Data Engineering

Data Engineering Jobs

3 jobs found

Today

Data Engineer - Contractor

System One Miamisburg, OH

Miamisburg, OH

Today

Contract Data Analysis Data Engineer Data Engineering

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Job Description

Contract Data Engineer role onsite supporting data integration, ETL, QA validation, and regulatory reporting for mortgage and banking platforms across Pittsburgh, PA; Farmers Branch, TX; Miamisburg, OH; and Houston, TX.

Responsibilities

Elicit business and technical requirements from multiple lines of business and source systems
Design, develop, and support data integration and database solutions across mortgage and banking platforms
Collaborate with QA teams on upfront testing and deployment validation activities
Coordinate with ETL and downstream technical teams to define data movement specifications
Assist with deployment activities into QA and Production environments
Ensure deployment documentation, validation, and operational processes are accurate and complete
Participate in data normalization, analysis, and process improvement initiatives
Support regulatory reporting and enterprise data aggregation efforts

Requirements

Hands-on experience with SQL
Experience with SQL Server
Experience with Oracle
Excellent verbal and written communication skills
Strong stakeholder interaction and requirement gathering experience
Ability to work independently and manage priorities effectively

Technologies

SQL
SQL Server
Oracle

NICE TO HAVE

Performance tuning or debugging experience
Banking or financial services domain experience
Experience supporting ETL/data movement processes

SOFT SKILLS

Strong communication and presentation skills
Self-driven and proactive mindset
Strong organizational and prioritization abilities
Ability to work effectively with business and technical stakeholders

ENVIRONMENT / TEAM

Team consists of Data Engineers and Quality Engineers
Heavy interaction with business users and technical teams
Focused on Home Lending Technology and Mortgage Data Platforms
Agile, collaborative, and fast-paced environment

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1d ago

Lead Generative AI Data Engineer III

Deloitte Atlanta, GA

Atlanta, GA

1d ago

$159k - $265k/yr Full time Manager Ai Workflows Anthropic

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Job Description

Location and compensation: This onsite role is based in Atlanta, GA, with a competitive salary range of USD 159,100 to 265,100 per year. It also includes a discretionary annual incentive program. You will join a role that emphasizes leadership in generative AI, collaboration across disciplines, and mentorship of peers.

Responsibilities

Lead the end-to-end lifecycle of machine learning and artificial intelligence solutions for business and client use cases, from design through deployment.
Oversee AI engineering workstreams by assigning tasks, reviewing outputs, and driving quality, timely delivery, and issue resolution across the team.
Build and manage data pipelines, model training workflows, and production‑grade components that support AI enabled products.
Partner with engineers, data scientists, product stakeholders, and business teams to translate requirements into scalable technical solutions and guide key technical decisions.
Coach and mentor junior practitioners, provide day‑to‑day guidance, and monitor model and application performance to improve accuracy, reliability, and scalability.

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field.
7+ years of professional experience.
5+ years designing, developing, or deploying machine learning, artificial intelligence, or advanced analytics solutions.
3+ years programming in Python, PySpark, PyTorch, and TensorFlow.
2+ years of technology consulting experience in the Federal Health space.
2+ years deploying machine learning models into production environments.
2+ years leading technical teams, projects, or workstreams supporting AI or ML solution delivery.
1+ year working with AI technologies such as Gemini, Anthropic, and OpenAI.
Active certification or advanced certification in Python, PySpark, PyTorch, and TensorFlow.
Ability to travel approximately 20% based on client needs and engagements.
Legal authorization to work in the United States without employer sponsorship, now or in the future.

Technologies

Python
PySpark
PyTorch
TensorFlow
Docker
Kubernetes
Gemini
Anthropic
OpenAI

Benefits

Discretionary annual incentive program

Skills for success

Ability to work independently and collaboratively within a team
Effective written and verbal communication
Meticulous attention to detail and quality of work
Proven ability to build and sustain professional relationships
Capacity to lead projects or workstreams
Strong multitasking and prioritization in a fast-paced environment
Professional interpersonal skills and demeanor
Reliability in meeting deadlines
Experience mentoring others and providing clear guidance

Preferred

Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field
Active US Government security clearance
2+ years experience with large language models, natural language processing, or generative AI solutions
2+ years using containerization and orchestration tools such as Docker or Kubernetes
1+ years supporting model monitoring, governance, or MLOps processes

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1d ago

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

Salesforce San Francisco, CA

San Francisco, CA

1d ago

$149k - $286k/yr Full time AI Data Engineer Data Engineering

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Job Description

Overview

Salesforce stands as a leader in AI powered customer relationship management, driven by teams of agents delivering customer success. We seek ambitious professionals who want to advance business and society through AI while upholding Salesforce’s core values. If you are excited about the future of AI in enterprise settings, this opportunity is for you.

The Opportunity

Salesforce is building the next generation Enterprise Knowledge Graph platform to empower AI driven experiences, agent centered applications, semantic search, enterprise data discovery, and intelligent decision making across the organization. We are hiring for both a Senior Member of Technical Staff (SMTS) and a Lead Member of Technical Staff (LMTS) to join the Enterprise Knowledge Graph and AI Engineering team.

Your Responsibilities

Design and Implement: Develop and scale the Enterprise Knowledge Graph platform components with a focus on performance, throughput, reliability, high availability, and data integrity. LMTS leads hands on design and subsystem implementation; SMTS contributes production grade code.
Graph and Ontology Engineering: Create graph data models, craft complex queries, and build scalable data pipelines to map structured and unstructured data to enterprise ontologies and taxonomies. LMTS also designs enterprise ontologies, taxonomies, semantic layers, entity resolution frameworks, graph APIs, and vector search capabilities to support advanced RAG and agentic workflows.
Semantic Routing: Develop Python based semantic routing frameworks to parse, classify, and dynamically direct incoming queries to the appropriate knowledge graph indexes or vector databases. LMTS designs, optimizes, and productionizes routing frameworks at scale, steering queries to relevant graphs, ontology subgraphs, or vector stores.
AI Tooling and Automation: Build and integrate AI powered developer tools and engineering automation platforms leveraging ecosystems such as Claude, Cursor, Windsurf, AI Agents, and Model Context Protocol (MCP) frameworks. LMTS also develops, deploys, and optimizes these tools and drives strategy and productionization.
Data Integration: Create scalable data pipelines and engineering patterns to ingest, transform, and orchestrate structured, unstructured, and third party data sources into graph based platforms mapped to enterprise ontologies.
Feature Ownership and Technical Execution: Own the technical delivery of specific platform features from concept through design, coding, testing, and production deployment. LMTS translates high level technical visions into concrete system blueprints, ontology schemas, and execution plans.
Code Quality and Rigor: Engage in code reviews, write comprehensive automated unit and integration tests, and uphold engineering standards and operational best practices.
Technical Mentorship: Provide technical guidance to the engineering team. SMTS mentors MTS and Associate engineers; LMTS offers day-to-day guidance, code reviews, and design direction to SMTS, MTS, and associated engineers to foster technical rigor and operational maturity.
Cross-Functional Collaboration: Work closely with Lead and Principal Engineers, Product Managers, and Data Engineering teams to deliver robust features aligned with enterprise AI priorities. LMTS also partners with PMTS engineers and Ontology governance boards to ensure alignment with AI infrastructure standards.
Evaluate and Innovate: Conduct deep dive evaluations of emerging graph technologies, ontology modeling tools, semantic reasoning frameworks, vector databases, and AI tooling to continuously modernize the platform.

You're Our Person If

SMTS

Experience: 8+ years of hands on software engineering experience in development, data engineering, distributed systems, or enterprise data platforms.
Education: A related technical degree is required.
Core Programming: Expert level backend coding skills with strong fluency in Python and standard object oriented or functional programming languages.
Semantic Routing and AI: Hands on experience building and deploying custom semantic routers using Python, embeddings, LangChain, or cosine similarity, alongside Retrieval-Augmented Generation architectures, vector search platforms, and AI workflows.
Graph and Ontology Fundamentals: Solid experience with graph databases and semantic web concepts such as Neo4j, RDF/OWL, SPARQL, and property graphs, mapping data to structured taxonomies.
Developer Tooling: Practical experience configuring, testing, or integrating AI-assisted engineering tools or automation workflows such as Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks.
Distributed Systems and Cloud: Proven ability to build cloud native applications on AWS, GCP, or Azure using microservices, REST or gRPC APIs, and event driven data streaming (Kafka).
Delivery: A track record of owning and delivering complex features in an agile production environment.

LMTS

Experience: 10+ years of hands-on experience in software engineering, data engineering, distributed systems, or enterprise data platforms.
Education: A related technical degree is required.
Ontology and Graph Expertise: Substantial hands-on experience designing and building Knowledge Graph platforms, formal ontologies, semantic models, taxonomies, or enterprise metadata management systems.
Tooling and Ecosystems: Strong hands-on experience with graph technologies and ontology engineering tools such as Neo4j, TopQuadrant, Protégé, RDF/OWL, SPARQL, SHACL, property graphs, and semantic reasoning frameworks.
AI and Retrieval: Proven experience implementing graph powered AI solutions, vector search platforms, Retrieval-Augmented Generation architectures, and orchestrating agentic workflows.
Semantic Routing Mastery: Demonstrated hands-on experience designing, optimizing, and productionizing custom semantic routing.

Location

San Francisco, California 94105

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Data Engineering Jobs

Data Engineer - Contractor

Lead Generative AI Data Engineer III

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

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