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About the Role
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.
Responsibilities
- 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.
Requirements
- 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.
Skills
- AWS
- Data Engineering
- Cloud-based data solutions
- Data pipelines
- Data lakes
- Data warehouses
- Automation
- Analytics
- Business Intelligence
- Machine Learning
- S3
- Redshift
- Glue
- Athena
- EMR
- DynamoDB
- Lambda
- Kinesis
- ETL/ELT
- Python
- Spark
- Scala
- AWS Glue
- EMR
- Snowflake
- CI/CD pipelines
- Infrastructure-as-Code
- Terraform
- CloudFormation
- DevOps
- CloudWatch
- IAM
- KMS
- VPCs
- Secrets Manager
- Data governance
- Data privacy
- Audit
- Regulatory requirements
- SQL
- Kafka
- Airflow
Location
- Whippany, NJ
Work Type
- Onsite
- Hybrid
Experience Level
- 5+ years of experience in data engineering and cloud-based data platforms.
Education Level
- Bachelor's degree in Computer Science, Information Technology, Engineering, or related field.
Salary/Compensations
- 78628-95278
Benefits
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 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
About the Company
- Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
Equal Opportunity
- All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.