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
Engineer
ETL
Hr Technology
Informatica
Information Technology (IT)
Microsoft
Power BI
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Programming
Programming Language
Programming Languages
Reporting and Analytics
Spark
SQL
Visual Design
Job Description
Capgemini Sogeti is looking for a Data Engineer to help design, build, and optimize scalable data pipelines and data architectures on the AWS cloud platform. In this onsite role in New York, NY, you will contribute to ETL/ELT workflows, batch and real-time processing, and the controls that keep data reliable, governed, and usable for teams across the organization.
This position offers a USD 70,000 - 95,000 per yearly salary range and is well suited for professionals with at least 3 years of data engineering experience and a background in computer science or related fields.
What you’ll do
- Design, develop, and maintain scalable ETL/ELT data pipelines using AWS services
- Develop and optimize both batch and real-time data processing systems
- Ensure data quality, integrity, and governance across systems
- Partner with stakeholders to translate business requirements into technical solutions
- Implement data integration solutions across multiple sources and formats
- Monitor and troubleshoot data workflows to maintain 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
- Solid understanding of data modeling, warehousing, and big data concepts
- Familiarity with distributed processing frameworks: Spark and Hadoop
- Experience with CI/CD pipelines and version control (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
Benefits
- Paid time off based on employee grade (A-F), with Vacation 12-25 days depending on grade, plus company paid holidays, personal days, and sick leave (as defined by policy)
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (for example, 401(k) in the U.S. or RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
Preferred qualifications and focus areas
- Experience with Apache Spark, Kafka, or Databricks
- Knowledge of data governance, security, and compliance
- Familiarity with infrastructure as code (Terraform, 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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