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Open nowPosted 18 days ago

Data Engineer (AWS, Spark)

Workable (global search)109,826 open roles

Where
Washington, DC, United States
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Your applicationOpen nowData Engineer (AWS, Spark)Workable (global search) · Washington, DC, United States

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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 2 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 18 days ago

Workable (global search) median: 2 days open

The posting

At Peregrine Advisors, you will build the pipelines that move a federal agency's data from source to platform. But we hire people, not seats. As the work evolves, you will learn new systems and tools, take on greater responsibility, and help develop the firm's capabilities, tools, and lines of business. We move our best to where the hardest problems are.

This is a hybrid work arrangement based in the Washington, DC metropolitan area, and the commuting cadence varies by assignment. The initial engagement requires United States citizenship and the ability to obtain a Public Trust determination.

We are a data and technology innovation hub and a Benefit Corporation working at the center of the federal government's mission to deliver for client stakeholders and the US public.

Your first project

Your first project will likely have you building ingest, processing, and storage at scale. Depending on the assignment, you may:

  • Build Spark-based extract, transform, and load (ETL) pipelines with Glue, Amazon EMR, Lambda, and Step Functions.
  • Write the processing in Python and PySpark.
  • Design the S3 layer, including Parquet, partitioning, and lifecycle, feeding Apache Iceberg tables.
  • Connect PostgreSQL on Amazon Aurora and DynamoDB, with Trino for federated Structured Query Language (SQL) across them.

You deliver pipelines that keep data clean and trustworthy at the volumes a federal platform runs at. You automate ingestion that used to be handled case by case, and you build the storage design everything downstream depends on.

This is where you start, not the shape of your career here.

Requirements

  • 4+ years of data engineering experience
  • Bachelor's degree
  • Spark ETL on AWS (Glue, Amazon EMR) in Python and PySpark
  • S3 data-lake design (Parquet, partitioning, lifecycle) feeding Apache Iceberg tables, Amazon Aurora PostgreSQL, and DynamoDB
  • Event orchestration (Lambda, Step Functions, SQS/SNS) with secrets management and monitoring
  • Data quality, validation, and lineage
  • Infrastructure-as-code (CloudFormation or Terraform)
  • Basic proficiency in writing, PowerPoint, and Excel

Preferred

  • Master's degree in a relevant field
  • Trino or comparable federated SQL across the lake and relational stores
  • Apache Ranger-governed access
  • Legacy ETL migration (for example DataStage)
  • Federal information technology or high-volume data experience
  • Familiarity with AI-assisted developer tooling

Who you are

You are a data engineer who wants to get better at it, and you know which parts you have not mastered yet. You care as much about whether the data is trustworthy as whether it arrives, and you do your best work alongside people who push you. You experiment, fail, learn, and repeat quickly. You would rather own an outcome than be handed a task.

What you bring

  • Hands-on data engineering on AWS: Spark ETL (Glue, EMR), Python and PySpark, and S3 data-lake design feeding the platform stores.
  • The reliability craft around it: event orchestration, data quality and lineage, monitoring, and infrastructure-as-code.
  • The judgment to build in a regulated environment where accuracy and auditability are not optional.

You adapt your development workflow as AI tools evolve, using them to help implement, test, and improve the components you own. You give the tools clear context, review and test their output, and remain accountable for the code you deliver.

When we talk

Be prepared to discuss a difficult problem you worked through, the decisions you made, what happened, and what you learned.

Benefits

This is a full-time W-2 position with a salary of $103,000 to $140,000 per year.

Benefits include medical, dental, and vision insurance with the employee premium fully paid and half of dependent premiums; employer-paid life, accidental death, and short-term and long-term disability insurance; a 401(k) matched 100% up to 4% of salary, vesting immediately; unlimited paid time off; and sponsored professional certifications and continuing education.

What we offer

You will work alongside developers, engineers, data scientists, architects, and strategists, on work ranging from strategy to implementation. We support your development across assignments and clients through extensive onboarding, sponsored professional certifications such as the Data Management Capability Assessment Model (DCAM) and AWS technical certifications, and rotation across functions to expand your skills and perspective. The mission is real, the problems are hard, and you own what you ship.

What we commit to

As a Benefit Corporation, our commitment runs three ways: real, measurable value for our clients; government that works better for the public; and a team that makes everyone in it better.

We hire people who want to help build the firm, not just work at it. If that is you, apply.

Peregrine Advisors is an equal opportunity employer.

Peregrine exclusively works with OPEN Data Jobs to recruit our team. Register with OPEN Data Jobs to be considered for this and future openings.

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