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Capgemini

Global consulting, technology services, outsourcing

AWS Data Engineer

Data EngineeringUpdated on Nov 14
Full-timeHanover, NJ, USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Technology, Engineering, or a related field is required.
  • At least 5 years of experience in Data Engineering and cloud-based data platforms is required.
  • Strong hands-on experience with AWS data services, including S3, Redshift, Glue, Athena, EMR, and DynamoDB, is required.
  • Proficiency in Python, SQL, Spark, and ETL/ELT development is required.
  • Experience building and managing data lakes, data warehouses, and modern data platforms is required.
  • Knowledge of Kafka, real-time data processing, and distributed data architectures is required.
  • Experience with Terraform, CloudFormation, CI/CD pipelines, and DevOps practices is required.
  • A strong understanding of data modeling, database optimization, and performance tuning is required.
  • Excellent analytical, problem-solving, and communication skills are required.

Responsibilities

  • Design and implement scalable data architectures using AWS services, including 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 pipelines using AWS Glue, Lambda, Kinesis, and Kafka.
  • Use Spark on EMR or Glue, Python, and Scala to develop data transformation workflows.
  • Implement data quality checks, validation rules, and automated error-handling mechanisms.
  • Build and maintain data lakes on Amazon S3 and data warehouses on Redshift and Snowflake.
  • Design and optimize data models, database schemas, partitioning strategies, and query performance.
  • Manage metadata, data cataloging, and lineage using AWS Glue Data Catalog and related tools.
  • Implement CI/CD pipelines using CodePipeline, CodeBuild, GitHub Actions, or Jenkins.
  • Automate infrastructure provisioning using Terraform, CloudFormation, and Infrastructure-as-Code practices.
  • Monitor and support data pipelines and cloud infrastructure using CloudWatch, CloudTrail, and AWS Config.
  • Apply AWS security best practices, including IAM, KMS encryption, VPC networking, and Secrets Manager.
  • Troubleshoot pipeline failures, performance bottlenecks, and data quality issues, and provide technical guidance on AWS data architecture best practices.

Desired Qualifications

  • AWS Certified Data Engineer, AWS Certified Solutions Architect, or related AWS certifications are preferred.
  • Experience with Snowflake and Lakehouse architectures is preferred.
  • Familiarity with Airflow, Databricks, and modern data engineering frameworks is preferred.
  • Experience supporting analytics, business intelligence, and machine learning workloads is preferred.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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