Data Engineer
Analytics
Big Data
Bigdata
Business Analytics
Business Intelligence
Cloud Data Engineering
Cloud Data Platform
Cloud Platform
Cloud Platforms
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Engineering
Data Integration
Data Pipeline
Data Platform
Data Processing
Data Visualization
Data Warehouse
Database
Databases
Databricks
Design
Digital Marketing
ETL
Hr Technology
Informatica
Information Technology (IT)
Microsoft
Power BI
Power Platform
Programming
Programming Language
Programming Languages
Reporting and Analytics
Spark
SQL
Visual Design
Job Description
What you can expect
Capgemini Sogeti supports data engineering work that connects scalable cloud infrastructure with reliable data flows. This role is based in New York, NY (onsite) and offers a salary range of USD 70,000 - 95,000 per year. You will design, build, and optimize data pipelines and architectures across AWS, with collaboration across data science, analytics, and DevOps teams.
Benefits and support
- Paid time off based on employee grade (A-F), defined by policy: Vacation 12-25 days depending on grade, Company paid holidays, Personal Days, and Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans such as 401(k) in the U.S. (or RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Additional benefits as provided by local policy and eligibility
Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines using AWS
- Develop and optimize batch and real-time data processing systems
- Ensure data quality, integrity, and governance across systems
- Translate business requirements into technical solutions with stakeholders
- Implement data integration across multiple sources and formats
- Monitor and troubleshoot data workflows for performance and reliability
- Optimize costs and performance of AWS/GCP data infrastructure
- Collaborate with data scientists, analysts, and DevOps teams
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field
- 3-8+ years of experience in data engineering or related roles
- Proficiency in SQL and at least one programming language: Python, Scala, or Java
- Experience with ETL tools and frameworks
- Strong understanding of data modeling, warehousing, and big data concepts
- Familiarity with distributed processing frameworks such as Spark and Hadoop
- Experience with CI/CD pipelines and version control using Git
Technologies you may work with
AWS, GCP, Databricks, Snowflake, dbt, SQL, Python, Scala, Java, ETL tools, Spark, Hadoop, Git, CI/CD pipelines, Kafka, Terraform, CloudFormation, Power BI, Tableau
Preferred qualifications
- Experience with Apache Spark, Kafka, or Databricks
- Knowledge of data governance, security, and compliance
- Familiarity with infrastructure as code such as Terraform and CloudFormation
- AWS certifications such as AWS Certified Data Engineer or Solutions Architect
- Experience with BI tools including Power BI and Tableau
Key competencies
- Strong problem-solving and analytical skills
- Excellent communication and collaboration abilities
- Attention to detail and a commitment to data quality
- Ability to work in a fast-paced, agile environment
Nice to have
- Experience with machine learning data pipelines
- Knowledge of real-time analytics and streaming architectures
- Exposure to multi-cloud or hybrid environments
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