Atlanta, GA

Engineer Jobs in Atlanta, GA

169 jobs found

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1mo ago

Director, AI Engineer

Coca-Cola Atlanta, GA

Atlanta, GA

1mo ago Closed

$171k - $198k/yr Full time Manager Agentic Ai Ai Agent

This position is no longer accepting applications (closed Oct 18, 2026).

Job Description

The Director, AI Engineer will lead delivery, adoption, and continuous evolution of AI engineering capabilities for Fuelight 360, an enterprise resource allocation and investment optimization capability at Coca-Cola. This role reports to the Senior Director, AI Engineering Lead and partners across product, data science, engineering, and core technology to deliver production AI solutions and strengthen AI engineering maturity.

Key Responsibilities

Design, develop, and operationalize AI capabilities within Fuelight 360 by translating business and analytical needs into scalable production systems.
Evaluate and implement generative AI and agent-based solutions that enhance decision support, scenario planning, user guidance, and insight generation.
Convert enterprise AI strategy, architecture standards, and platform capabilities into Fuelight 360 roadmap items and implementation plans.
Provide technical direction on AI architecture, model integration patterns, and emerging AI technologies aligned to Fuelight product roadmap and long-term strategy.
Collaborate with Fuelight Product Managers, Technical Leads, Data Scientists, and Product Engineering leadership to prioritize and deliver high-value AI use cases.
Ensure MLOps, LLMOps, and AgentOps practices are effectively implemented, including lifecycle management, deployment automation, observability, monitoring, and operational governance.
Drive adoption of enterprise AI standards, reusable patterns, development tools, and engineering best practices across product teams.
Lead end-to-end design, development, deployment, and operations for production AI applications, LLM-powered products, and agent-based solutions.
Manage and develop AI engineering teams through coaching, technical leadership, performance management, and career development support.
Set engineering quality expectations via architecture reviews, code reviews, testing practices, and operational readiness assessments.
Work with Core Technology to leverage enterprise AI platforms, orchestration services, and foundational capabilities while identifying improvement opportunities.
Ensure AI solutions meet enterprise governance, security, responsible AI, privacy, and risk management requirements.
Advance AI observability and operational excellence through monitoring, evaluation, performance optimization, and continuous improvement.
Support enterprise digital twin, forecasting, simulation, optimization, and intelligent automation initiatives.
Assess emerging AI technologies and engineering approaches, then recommend improvements to delivery effectiveness and business impact.
Promote a culture of experimentation, learning, collaboration, and engineering excellence within AI engineering teams.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related technical discipline.
8+ years of experience in software engineering, AI engineering, machine learning engineering, platform engineering, or related technical fields.
5+ years of experience leading engineering teams, serving as a technical lead, or operating in specialized engineering leadership roles.
Proven experience delivering production AI solutions, including generative AI, large language model applications, intelligent agents, and machine learning systems.
Experience leading delivery across multiple products or business domains in a matrixed environment.
Strong expertise in agentic AI architectures, Retrieval-Augmented Generation (RAG), GraphRAG, semantic search, vector databases, knowledge graphs, and AI orchestration frameworks.
Hands-on technical capability in Python and cloud-native application development (Azure preferred).
Experience implementing and operating MLOps, LLMOps, and AgentOps in production environments.
Experience establishing engineering standards, reusable frameworks, development accelerators, and operational best practices.
Knowledge of responsible AI, cybersecurity, privacy requirements, model governance, and enterprise risk controls.
Leadership experience coaching engineers and driving organizational capability growth.
Strong communication, stakeholder management, and influencing skills.
Business acumen with the ability to connect technical delivery to measurable business outcomes.

Technologies

Artificial Intelligence, Machine Learning, GenAI, Generative AI
Agent-based solutions, Large language model applications, Intelligent agents
MLOps, LLMOps, AgentOps
Python, Azure
Retrieval-Augmented Generation (RAG), GraphRAG, semantic search
Vector databases, knowledge graphs, AI orchestration frameworks
Digital twin, forecasting, simulation, optimization, intelligent automation

Location and Work Details

Location: Atlanta, GA (onsite)
Travel: 0% - 25%
Relocation Provided: Yes

Compensation and Incentives

Base Pay Range (United States): $171,000 - $198,000 per year
Annual Incentive Reference Value: 30%
Long-Term Incentive Reference Value: 0% - 20%

Additional Information

Job Posting End Date: September 27, 2026
Employment Authorization: The Coca-Cola Company will not offer sponsorship for employment status (including H1-B and other employment-based nonimmigrant visas). Applicants must be currently authorized to work in the United States on a full-time basis and must not require sponsorship to continue working legally in the United States.

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1mo ago

Senior Data Analytics Engineer

Mercedes-Benz Financial Services USA LLC Atlanta, GA

Atlanta, GA

1mo ago Closed

Full time Manager Senior Analytics

This position is no longer accepting applications (closed Oct 18, 2026).

Job Description

In this onsite role in Atlanta, GA, the Senior Data Analytics Engineer partners closely with business stakeholders and technology teams to deliver reporting, analytics, and decision-support solutions. Working as the data and analytics domain lead, you will help set requirements and define the metrics that matter, then translate them into analytical data models and reporting datasets that enable scalable self-service analytics across the organization.

Role focus

Lead the design and delivery of reporting, analytics, and data visualization solutions through stakeholder partnership, requirements gathering, business metric definition, data analysis, and support for decision-making adoption.
Design, develop, and maintain analytical data models, reporting datasets, semantic structures, and reusable analytics assets to support consistent, accurate, and scalable self-service analytics.
Serve as the data and analytics domain lead across business and technology initiatives by assessing impacts, defining requirements, guiding solution design, and supporting successful delivery.
Provide technical leadership, mentorship, and day-to-day coordination for team members and contractors, including prioritization of demand, resource allocation, solution reviews, and development standards and best practices.
Support compliance by promoting adherence to A22 - Global Data & Information Policy, maintaining required documentation, and providing complete, accurate, and timely information for audits, risk reviews, and regulatory reporting.

Experience and education requirements

Minimum: 5+ years of overall work experience.
Authorization: Applicants must be legally authorized to work in the U.S. at the time of application.
Relocation: Relocation assistance will not be provided.
Education: Bachelor’s Degree required; Master’s Degree preferred. Recommended majors include Accounting or Business Administration.
Preferred experience: Business-General (5 years); Finance (2 years); Information Technology (1 year).
Business intelligence foundations (minimum 5 years): Reporting, analytics, and data visualization concepts.
Data management depth (minimum 5 years): Data warehousing, dimensional modeling, semantic modeling, and enterprise data management practices.
Domain exposure (minimum 5 years): Business processes and data domains such as Finance, Credit, Collections, Client Services, Risk, or similar operational functions.
Analytics platforms (minimum 5 years): Modern analytics platforms, cloud-based data environments, and self-service analytics concepts.

Skills and qualifications

Ability to collect data, establish facts, and identify trends and variance.
Analytical and facilitation skills.
Programming, testing, and database knowledge, plus application development experience.
PC skills: Microsoft Office.
Experience with SAP.
Presentation and problem-solving skills.
Project management experience as a project leader and team member.
Business requirements: 5+ years gathering, analyzing, and documenting requirements and translating them into reporting, analytics, and data solutions.
SQL: 5+ years writing and optimizing complex SQL queries, plus data analysis, validation, and troubleshooting.
Modeling and assets: 3+ years designing and supporting analytical data models, semantic models, reporting datasets, and reusable analytics assets.
Visualization platforms: 3+ years with enterprise analytics and visualization platforms such as Power BI, Tableau, or similar; experience with Microsoft Fabric and Azure analytics services preferred.
Data analysis automation: 2+ years using Python, R, or similar tools for data analysis, automation, data profiling, or advanced analytics.
Stakeholder communication: 3+ years presenting analytical findings, facilitating discussions, and communicating with business and technical stakeholders.
Cross-functional leadership: 3+ years leading analytics initiatives, coordinating cross-functional teams, and mentoring team members.

Tools and technologies

Power BI, Tableau, Microsoft Fabric, Azure
Microsoft Office, SAP, SQL
Python, R

Preferred certifications

Microsoft Certified: Power BI Data Analyst Associate
Microsoft Certified: Fabric Analytics Engineer Associate
Microsoft Certified: Azure Data Engineer Associate
Equivalent certifications in business intelligence, analytics, data engineering, data management, or cloud data platforms may be substituted.

Benefits

Competitive salary plus an annual bonus based on company performance and/or personal yearly performance
Fifteen (15) additional corporate holidays
Mercedes-Benz Employee Lease Program
Outstanding medical, dental, and vision insurance
Employer-paid short and long term disability plus on-site exercise facilities
Six Weeks for New Parents (paid Family Leave Programs)
Adoption Expense Reimbursement Programs up to $6k per child
Tuition Assistance Scholar Program with up to $8k in vouchers for business-related coursework
401(K) with match
Mercedes-Benz car program
Flexible work arrangements
Mitarbeiter Events
Mitarbeiterrabatte möglich
Mitarbeiterhandy möglich
Mobilitätsangebote
Betriebliche Altersversorgung
Gesundheitsmaßnahmen
Coaching

Contact

Mercedes-Benz Financial Services USA LLC
One Mercedes-Benz Drive, 30328 Atlanta
NAFTA SSC E-Mail: nafta_ssc_recruiting@mercedes-benz.com

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1mo ago

Data Engineer III - Python/PySpark/Databricks/AI

JPMorganChase Atlanta, GA

Atlanta, GA

1mo ago Closed

Full time Python Artificial Intelligence Data

This position is no longer accepting applications (closed Oct 18, 2026).

Job Description

Join an agile team supporting trusted data collection, storage, access, and analytics solutions with enterprise-authorized AI tools.

Responsibilities

Support review of controls to help ensure sufficient protection of enterprise data
Advise and implement custom configuration changes in one to two tools to deliver requested products for business or customer needs
Update logical or physical data models as new use cases emerge
Use SQL regularly, with an understanding of NoSQL databases and where they fit in the market
Develop, test, and maintain critical data pipelines and architectures using SQL/NoSQL
Apply enterprise-authorized AI capabilities to accelerate data pipeline and design analysis and documentation, including:
- Validate AI outputs
- Handle data according to sensitivity and security requirements
Use reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines, including:
- Test generation
- Control validation
- Maintaining traceability/auditability
- Alignment to resiliency and security expectations

Requirements

3+ years applied experience plus formal training or certification in data engineering concepts
Experience across the data lifecycle
Advanced SQL skills (including joins and aggregations)
Working understanding of NoSQL databases
Demonstrated experience using enterprise-authorized AI capabilities in data engineering workflows, with:
- Strong validation habits
- Awareness of data sensitivity
Ability to review and validate AI-assisted outputs (examples include query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements
Significant experience with statistical data analysis, including selecting appropriate tools and data patterns for analysis
Experience customizing changes in a tool to generate a product

Technologies

SQL
NoSQL
AI
Python
PySpark
Databricks

Benefits

Comprehensive health care coverage
On-site health and wellness centers
A retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching

Preferred Qualifications

Exposure to cloud technologies
Exposure to AI-driven development

Location: Atlanta, GA (onsite)

Experience: 3+ years

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1mo ago

Data Engineer - PySpark and Apache

Infosys Atlanta, GA

Atlanta, GA

1mo ago Closed

Full time Big Data Bigdata Data

This position is no longer accepting applications (closed Oct 18, 2026).

Job Description

Opportunity in Atlanta, GA (onsite) with a role focused on delivering reliable software across the full SDLC. You will work as a Technology Consultant 2 supporting requirements, design, coding, testing, production support, and knowledge documentation, helping ensure smooth transitions to new software applications.

What you’ll do

Support requirements elicitation by documenting assigned portions of business requirements according to provided guidance.
Lead and contribute to application design discussions, documenting design decisions that help the technical team build the right solutions.
Participate in coding and integrate new features or updates into existing applications, with emphasis on system stability.
Perform code reviews, apply changes to the codebase, and maintain code repositories.
Help define and execute test strategies, analyze results, and coordinate bug fixes to maintain software quality standards.
Create user training programs, documentation, and support frameworks that enable a smooth shift to new applications.
Participate in resolving production issues and recommend preventive measures to strengthen system reliability.
Maintain detailed records covering code, testing approaches, and support activities to enrich the knowledge base and support other similar projects.

What you bring

Collaborative mindset and excellent communication skills.
Ability to manage end-to-end SDLC activities from requirement gathering through implementation.
Skill in translating complex requirements into actionable development tasks.
Strong interest in design along with hands-on coding experience.
Proactive approach to testing, troubleshooting, and improving applications.
Experience working with cross-functional teams and supporting software integration.

In this role, you will contribute throughout the lifecycle of software delivery, from aligning on requirements and design decisions to maintaining quality through testing and supporting production reliability.

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1mo ago

Lead Data Engineer

Norfolk Southern Corp Atlanta, GA

Atlanta, GA

1mo ago Closed

Full time Big Data Bigdata Cloud Data Engineering

This position is no longer accepting applications (closed Oct 18, 2026).

Job Description

Lead the engineering direction and delivery of a Databricks-based lakehouse, including streaming analytics capabilities.

Responsibilities

Define the data architecture with team and stakeholders, setting technical direction for lakehouse, ingestion, and transformation patterns
Identify, escalate, and remove technical blockers through hands-on problem solving, design decisions, and coordination across teams
Design and build enterprise data models (conceptual, logical, physical) across domains, aligned to lakehouse and pipeline architecture
Establish and enforce data modeling standards, best practices, and governance processes, including using Erwin
Define data requirements and perform wrangling of large scale structured and unstructured data, validating outputs by running tools in the data environment
Standardize and customize data analysis, develop mechanisms to ingest, analyze, validate, normalize, and clean data
Create data policies and develop interfaces and retention models, including synthesizing or anonymizing data
Implement statistical data quality procedures on new sources and support iterative analytics to enable data science and insights creation
Develop and maintain data engineering best practices, contributing to insights across data analytics and visualization concepts and techniques
Lead the data engineering team to build scalable data architecture and high-performance pipelines using state-of-the-art Big Data tooling
Build pipelines to clean, transform, and aggregate data from disparate sources
Use scripting languages and other tooling to connect systems together
Apply data architecture knowledge to lead project teams from requirements to implementation
Partner with data science and business intelligence teams on models and pipelines for research, reporting, and machine learning
Acquire and process high-velocity real-time and batch data across different sizes and scales

Requirements

10+ years in data engineering with deep, hands-on Databricks experience (Spark/PySpark pipelines, Delta Lake merges and schema evolution, Delta Live Tables, Unity Catalog governance)
Hands-on experience with Genie for self-service analytics and LakeFlow Designer for visual ETL orchestration
4+ years building reliable batch/streaming Spark workloads
3+ years with Kafka or Confluent for high-volume event processing
3+ years working with AWS analytics services (S3, IAM, Glue/Lambda/MSK)
Proven ability to design conceptual, logical, and physical data models with strong governance and advanced SQL skills for business-ready datasets
Track record leading technical design, mentoring engineers, driving architectural consensus, and unblocking teams on complex challenges
Experience delivering ETL/ELT pipelines end-to-end in a lakehouse environment and working within Agile frameworks (Scrum/Kanban/SAFe) to manage iterative delivery and cross-team dependencies

Technologies

Databricks, Spark, PySpark, Delta Lake, Delta Live Tables, Unity Catalog, Genie, LakeFlow Designer
Kafka, Confluent
AWS analytics services (S3, IAM, Glue/Lambda/MSK)
SQL, Erwin, Python, Scala
PySpark/Scala-Spark
Snowflake, BigQuery, HBase, Cassandra
Azure, Kinesis, TIBCO EMS, IBM MQ Series, MSK
GIT, REST API, Web Services, NoSQL
ETL/ELT, Agile frameworks (Scrum/Kanban/SAFe)

Work Conditions

Location: Atlanta, GA, US
Work model: Hybrid (two days in office; three days remote)
Shift work: No
On-call: Yes
Weekend work: No

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1mo ago

Lead Data Engineer - Snowflake

Capgemini Atlanta, GA

Atlanta, GA

1mo ago Closed

$165k - $190k/yr Full time Manager Artificial Intelligence Cloud

This position is no longer accepting applications (closed Oct 18, 2026).

Job Description

Capgemini is seeking an experienced Lead Data Engineer to help design and deliver enterprise-scale Data & AI platforms on Snowflake. In this onsite Atlanta role, you will take a lead role in building unified platform capabilities, improving performance and cost efficiency, and enabling data products that teams can use to power analytics and AI use cases.

Location: Atlanta, GA (onsite)
Compensation: USD 165,000 - 190,000 per year
Experience: 7+ years
Education: Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field

Responsibilities

Design and implement enterprise-wide Unified Data & AI Platforms leveraging Snowflake.
Architect and develop scalable Medallion Layer (Bronze, Silver, Gold) data models and frameworks.
Build and maintain high-performance ELT pipelines using: Snowflake Dynamic Tables, dbt, Tasks & Stored Procedures, Snowpipe, and Snowflake Openflow Connect.
Develop AI-powered solutions using the Snowflake Cortex ecosystem, including: Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, Python, Streamlit, and MLOps frameworks.
Design and implement secure, governed data environments using Snowflake Horizon.
Establish and maintain RBAC (Role-Based Access Control) and ABAC (Attribute-Based Access Control) frameworks.
Collaborate with business and technology teams to build customer-centric, domain-oriented data products.
Implement CI/CD processes and Git-integrated development workflows.
Monitor, optimize, and improve platform performance, scalability, and cost efficiency.
Partner with architects, data scientists, analysts, and business stakeholders to deliver data-driven solutions.
Ensure adherence to security, governance, compliance, and data quality standards.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
7+ years of experience in Data Engineering, Data Architecture, or Analytics Engineering.
Strong hands-on experience designing and implementing data platforms on Snowflake.
Proven expertise in Unified Data & AI platform architecture.
Proven expertise in Medallion architecture implementation.
Proven expertise in ELT/ETL pipeline development.
Proven expertise in data warehousing and data lake concepts.
Deep experience with: Snowflake Dynamic Tables, dbt, Snowpipe, Tasks, Stored Procedures, and Openflow Connect.
Hands-on experience with Snowflake AI and ML capabilities: Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, Streamlit, Python, and MLOps practices.
Strong understanding of Snowflake security, governance, and data management capabilities, including Horizon.
Experience implementing RBAC and ABAC security models.
Experience with Git-based source control and modern ELT frameworks.
Strong cloud platform experience with AWS.
Excellent communication, stakeholder management, and problem-solving skills.

Technologies

Snowflake, Snowflake Dynamic Tables, dbt, Tasks, Stored Procedures, Snowpipe, Snowflake Openflow Connect
Snowflake Cortex ecosystem: Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML
Python, Streamlit, MLOps frameworks
Snowflake Horizon, RBAC, ABAC, CI/CD, Git
AWS

Benefits

Paid time off based on employee grade (A-F): Vacation 12-25 days depending on grade, plus company paid holidays, personal days, and sick leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (for example, 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

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1mo ago

Snowflake Platform Admin + Data Engineer

Capgemini Atlanta, GA

Atlanta, GA

1mo ago Closed

$103k - $129k/yr Full time Automation Aws Data Lake Cloud

This position is no longer accepting applications (closed Oct 18, 2026).

Job Description

Capgemini is hiring a Snowflake Platform Admin + Data Engineer in Atlanta, GA with a hybrid work model. This role combines enterprise Snowflake platform ownership with hands-on data engineering, governance, and automation, with a salary range of USD 103,330 - 128,656 per year.

What you can expect

You will administer and support Snowflake environments across development, testing, and production, while building and optimizing ETL/ELT pipelines and implementing security and governance standards. The work includes automation and DevOps-style deployment support, along with ongoing performance, reliability, and cost improvements.

Key responsibilities

Administer and support enterprise Snowflake environments across development, testing, and production.
Manage Snowflake account setup, including user provisioning, roles, permissions, and RBAC.
Implement and maintain security controls such as SSO, MFA, dynamic data masking, row-level security, and secure data sharing.
Configure and monitor resource monitors, virtual warehouses, and workload management to optimize platform performance and cost.
Design and manage cross-region replication, disaster recovery, and business continuity solutions.
Monitor platform health, troubleshoot issues, and provide proactive recommendations for improvement.
Design, develop, and maintain scalable ETL/ELT pipelines using AWS Glue and Snowflake.
Build and optimize data ingestion frameworks from multiple cloud and on-premises data sources.
Develop data models, transformations, and data warehouse solutions for analytics and reporting.
Leverage Snowflake features such as Snowpipe, Streams, Tasks, Stored Procedures, Time Travel, and Zero-Copy Cloning.
Implement data quality, validation, and monitoring processes.
Analyze query performance and optimize Snowflake workloads, including tuning pipelines, SQL queries, and storage utilization.
Establish platform standards, governance policies, and best practices.
Develop CI/CD pipelines for Snowflake deployments and data engineering solutions.
Automate administrative and operational activities using Python, SnowSQL, and scripting frameworks.
Support Infrastructure as Code (IaC) initiatives using Terraform or similar technologies.

Required experience and skills

8+ years of IT experience, including 4+ years of hands-on Snowflake experience.
Strong expertise in Snowflake administration and platform management.
Hands-on experience with AWS Glue and cloud-based data engineering solutions.
Advanced proficiency in SQL and Python.

Helpful skills and certifications

Experience with Apache Airflow for orchestration.
Knowledge of Snowpark, Snowpipe, Data Sharing, and Native Applications.
Experience with Terraform and Infrastructure as Code.
Experience with CI/CD tools such as GitHub Actions, GitLab CI/CD, or Azure DevOps.
Snowflake certifications such as SnowPro Core Certification, SnowPro Advanced Architect, and SnowPro Advanced Data Engineer.
Experience with data governance, compliance, and enterprise security frameworks.

Benefits

Flexible work
Healthcare including dental, vision, mental health, and well-being programs
Financial well-being: 401(k) and Employee Share Ownership Plan
Paid time off and paid holidays, including Vacation (12-25 days depending on grade), Personal Days, Sick Leave (A-F) as defined by policy
Paid parental leave
Family building benefits including adoption assistance, surrogacy, and cryopreservation
Social well-being benefits such as subsidized back-up child/elder care and tutoring
Mentoring, coaching and learning programs
Employee Resource Groups
Disaster Relief
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada); retirement savings plans (401(k) in the U.S., RRSP in Canada); life and disability insurance; employee assistance programs; and additional benefits per local policy and eligibility