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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer (Aws, Spark - **Company:** PEREGRINE ADVISORS LLC - **Location:** Washington, DC, United States - **Experience:** Experienced - **Salary:** $103,000.0 - $140,000.0 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, Apache HTTP Server, Information Systems, Databases, Data Cleansing, Information Engineering, Extract Transform Load (ETL), IBM InfoSphere DataStage, Programming Tools, Amazon DynamoDB, Python (Programming Language), Key Management, PostgreSQL, Microsoft PowerPoint, Cadence Virtuoso, SQL Databases, Parquet, Scripting, Apache Spark, Electronic Medical Records, AWS Lambda, Cloudformation, Data Lakes, Pyspark, Information Technology, Data Management, Amazon Simple Queue Service (SQS), Terraform, Amazon Elastic Mapreduce (EMR) - **Published:** September 21, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-engineer-aws-spark-washington-dc--6c125432-a9e3-41cf-aef4-2fcee06738c9 ## About the Role * 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., AWS Lambda, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Apache, Artificial Intelligence (AI), Cadence, Data Analysis, Data Cleaning, Data Lake, Data Management, Data Quality, Data Science, Database Extract Transform and Load (ETL), Electronic Medical Records, Engineering, Federal Government, Government, Housekeeping/Cleaning, IBM WebSphere DataStage, Information Technology & Information Systems, Management Strategy, Microsoft Excel, Microsoft PowerPoint, Onboarding, PostgreSQL, Programming Tools, Python Programming/Scripting Language, SQL (Structured Query Language), Simple Queue Service (SQS), United States Citizen ## Description 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. 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