Data Engineer: III (Senior)

About

Our client is seeking a Senior Data Engineer with deep expertise in building scalable, cloud‑native data platforms on AWS. This is a hands‑on engineering role focused on designing and implementing modern lakehouse architectures using some AWS managed services, open table formats (Iceberg) and compute running in our EKS/ArgoWF environments.

Team Culture / Work Environment

• 4‑5 data teams
• They are all running through SAFe
• Sprints/deliverables
• Highly collaborative
• Fast pace
• Most of the team is hybrid
• Culture is ownership of the work and taking initiative

Daily Responsibilities

• Advanced Python Engineering Skills

  • Strong proficiency in Python for data engineering tasks.
  • Experience with modular, testable code and production‑grade pipelines.
  • Not looking for SQL‑heavy DBAs or analysts; this is a software engineering role.

• AWS Lakehouse Architecture Expertise

  • Proven experience designing and implementing lakehouse architectures on AWS.
  • Familiarity with key AWS services: S3, Glue, Athena, Glue Data Catalog, Lake Formation, QuickSight, CloudWatch, etc.
  • Experience with AWS QuickSight (Preferred), Tableau or Cognos.
  • ETL pipeline development.
  • Bonus: Experience with EKS‑based orchestration using EMR on EKS or Argo Workflows.

• Open Table Formats

  • Deep understanding of Apache Iceberg (preferred), Delta Lake, or Apache Hudi.
  • Experience implementing time‑travel, schema evolution, and partitioning strategies.

• Medallion Architecture Implementation

  • Experience designing and implementing Bronze, Silver, Gold data layers.
  • Understanding of ingestion, transformation, and curation best practices.

• Strong understanding of core data modeling concepts, including slowly changing dimensions (SCD Type 2) and their implementation in modern data platforms.

• Hands‑on experience with distributed computing frameworks such as Apache Spark or similar technologies.

• Experience with CI/CD tools and practices for building, testing, and deploying data pipelines.

• Strong communication and documentation skills.

• Ability to work independently and collaborate with cross‑functional teams including tech leads, architects, and product managers.

Degree or Certification Required?

• None

Years of Experience?

• 4‑5 years within data engineering / AWS

Nice to Haves

• Experience with DataOps practices and CI/CD for data pipelines.
• Familiarity with Terraform or CloudFormation for infrastructure‑as‑code.
• Exposure to data quality frameworks like Deequ or Great Expectations.
• Undergraduate degree.
• Iceberg on AWS