Senior AWS Data Engineer / Lead Data Engineer ***Fulltime Role***

  • McLean, VA
  • Posted 13 hours ago | Updated 13 hours ago

Overview

On Site
Depends on Experience
Full Time

Skills

AWS
Tableau
QuickSight
Power BI
Kubernetes

Job Details

Location: Mclean, VA
Job Type: Full-Time
Experience Level: 10+ Years
Industry: Finance

Job Summary:

We are seeking a highly experienced and motivated Senior AWS Data Engineer to join our data engineering team. The ideal candidate will have over 10 years of experience in data engineering, including extensive hands-on expertise with AWS cloud services, big data technologies, and data pipeline development. This role will play a critical part in designing, implementing, and optimizing scalable data solutions in a fast-paced, cloud-native environment.

Key Responsibilities:

  • Architect, build, and maintain high-performance data pipelines and ETL workflows using AWS services.

  • Design and implement data lake and data warehouse solutions on AWS using S3, Glue, Redshift, Athena, and Lake Formation.

  • Develop scalable and maintainable data ingestion frameworks from various structured and unstructured sources.

  • Optimize performance and cost-efficiency of existing cloud-based data infrastructure.

  • Work with data scientists, analysts, and business stakeholders to understand data needs and deliver robust data products.

  • Ensure data quality, data governance, and security standards are met across platforms.

  • Mentor junior engineers and provide technical leadership within the data team.

  • Collaborate with DevOps teams to enable CI/CD for data pipelines and ensure infrastructure as code (IaC) practices using tools like Terraform or CloudFormation.

Required Qualifications:

  • 10+ years of professional experience in data engineering, with at least 5+ years in cloud-native environments (AWS preferred).

  • Expertise in AWS data services: Glue, S3, Redshift, Athena, Lambda, EMR, Kinesis, Step Functions, etc.

  • Strong programming skills in Python and SQL. Familiarity with PySpark or Scala is a plus.

  • Experience with data modeling, data warehousing, and dimensional modeling.

  • Deep understanding of ETL/ELT processes, batch and streaming data workflows.

  • Hands-on experience with big data tools: Spark, Hive, Hadoop ecosystem.

  • Proficiency with version control (Git) and CI/CD pipelines (e.g., Jenkins, GitHub Actions).

  • Familiarity with infrastructure-as-code tools like Terraform, AWS CDK, or CloudFormation.

  • Strong understanding of data privacy regulations (e.g., GDPR, HIPAA) and best practices for data governance.

Preferred Qualifications:

  • AWS Certification: AWS Certified Data Analytics Specialty or AWS Certified Solutions Architect.

  • Experience with containerization (Docker, Kubernetes, ECS).

  • Familiarity with BI/Reporting tools (e.g., Tableau, QuickSight, Power BI).

  • Background in machine learning data support or real-time analytics is a plus.

  • Strong communication and stakeholder management skills.

Education:

  • Bachelor s or Master s degree in Computer Science, Engineering, Information Systems, or a related field.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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