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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # FSSBU - AWS Data Engineer - C1 - (BARC) - **Company:** Capgemini - **Location:** Hanover, NJ, United States - **Experience:** Expert - **Salary:** $78,628.0 - $95,278.0 - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Amazon S3, Data Analysis, Cloud Engineering, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, DevOps, Amazon DynamoDB, Identity and Access Management, Python (Programming Language), Machine Learning, Scala (Programming Language), SQL Databases, Unstructured Data, Data Processing, Cloud Platform System, Data Ingestion, Snowflake, Apache Spark, Database Performance, Electronic Medical Records, Cloudformation, Data Lakes, Information Technology, AWS Glue, AWS Data Analytics, Apache Kafka, Data Management, Functional Programming, Cloudwatch, Terraform, Stream Processing, Data Pipelines, Amazon Redshift - **Published:** August 29, 2026 - **Apply:** https://www.capgemini.com/jobs/542025-en_US_SAPBTP/x/ ## About the Role * Bachelor's degree in Computer Science, Information Technology, Engineering, or related field. * 5+ years of experience in data engineering and cloud-based data platforms. * Strong hands-on experience with AWS data services and cloud architecture. * Proficiency in Python, SQL, Spark, and ETL/ELT development. * Experience with Redshift, Snowflake, data lakes, and real-time data processing frameworks. * Knowledge of Terraform/CloudFormation, CI/CD pipelines, and DevOps practices. * Strong problem-solving, communication, and stakeholder management skills. Preferred Qualifications * AWS Certified Data Engineer, Solutions Architect, or related AWS certification. * Experience with Kafka, Airflow, and modern lakehouse architectures. ## Description We are seeking a skilled AWS Data Engineer to design, build, and maintain scalable cloud-based data solutions on AWS. The ideal candidate will have experience developing data pipelines, managing data lakes and warehouses, implementing automation, and ensuring secure, high-quality data platforms that support analytics, business intelligence, and machine learning initiatives., * Design and implement scalable data architectures using AWS services such as S3, Redshift, Glue, Athena, EMR, DynamoDB, Lambda, and Kinesis. * Build, optimize, and maintain ETL/ELT pipelines for structured and unstructured data. * Develop real-time and batch data ingestion solutions using AWS-native technologies and Kafka. * Utilize Python, Spark, Scala, AWS Glue, and EMR for data processing and transformation. * Build and manage data lakes on Amazon S3 and data warehouses on Redshift or Snowflake. * Optimize data models, database performance, partitioning, and storage strategies. * Implement CI/CD pipelines, Infrastructure-as-Code (Terraform/CloudFormation), and DevOps best practices. * Monitor and troubleshoot data pipelines, infrastructure, and performance issues using CloudWatch and related AWS services. * Apply AWS security best practices, including IAM, KMS, VPCs, and Secrets Manager. * Ensure compliance with data governance, privacy, audit, and regulatory requirements. * Collaborate with data scientists, analysts, and business stakeholders to deliver scalable data solutions. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Tips, Techniques, and Common Pitfalls Debugging Kafka](https://www.wearedevelopers.com/videos/838-tips-techniques-and-common-pitfalls-debugging-kafka) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Best Coding Boot Camps in Germany](https://www.wearedevelopers.com/magazine/237-best-coding-boot-camps-in-germany) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)