The work centers on building secure, well-structured data pipelines and data models in AWS, using Python, PySpark and SQL day to day. What You Will Do Write and tune PySpark, Python and SQL processing jobs so they run fast, stay stable, and are easy for the next engineer to maintain.
Numbers & Facts
Location
Washington, DC
Salary
$20,000–$260,000 Per Year
Description
AWS Data Engineer
Location: Washington, DC metro area (onsite) Clearance: Active TS/SCI required Citizenship: U.S. citizen required Overview
We are hiring an AWS Data Engineer for an onsite federal program in the Washington, DC area. The work centers on building secure, well-structured data pipelines and data models in AWS, using Python, PySpark and SQL day to day. You should have 5+ years in data engineering, at least 3 of them working in AWS. What You Will Do
Write and tune PySpark, Python and SQL processing jobs so they run fast, stay stable, and are easy for the next engineer to maintain.
Stand up and manage ETL and ELT pipelines that pull structured and semi-structured data from a range of upstream systems.
Put production pipelines under proper observability, with validation rules, logging, monitoring and alerts.
Build and keep improving AWS data solutions across S3, Glue, Athena, EMR, Redshift, Lambda and Step Functions.
Own lake and warehouse modeling, including schema design, partition strategy and catalog management.
Meet with business and technical users to capture requirements, chase down defects and write up how things work.
Hold every workload to federal security expectations: IAM controls, encryption and least-privilege access.
Contribute to CI/CD and infrastructure-as-code for the data platform.
What You Bring
8+ years of total professional experience, with 5+ in data engineering or ETL development
3+ years hands-on with AWS data services (Glue, S3, Lambda, Redshift, Athena, EMR)
Advanced Python and SQL, plus working experience with Spark/PySpark
A track record running production ETL against large data volumes
Good command of dimensional modeling, warehouse design and data lake patterns
Comfort working in Agile teams with Git for version control
Ability to explain technical work clearly to engineers and non-technical users alike
Bachelor's in Computer Science, Information Systems, Engineering or a related field, or equivalent experience
Nice to Have
Streaming experience with Kafka or Kinesis
Terraform or CloudFormation
Exposure to Snowflake, Databricks or Informatica
Workflow orchestration with Airflow (MWAA) or Step Functions
An AWS certification such as Data Engineer Associate or Solutions Architect
Prior federal work, ideally involving financial regulatory data
Background in FedRAMP or other compliance-heavy environments