Associate Performance Engineer

eSimplicity•Columbia, MD

1d•$93,000 - $136,400•Hybrid

About The Position

eSimplicity is seeking an Associate Performance Engineer with performance engineering expertise to support a federal financial regulatory agency's cloud-based enterprise data platform. In this role, you will assist with tuning, troubleshooting, load-testing large-scale data pipelines and querying workloads across AWS Glue/PySpark, MWAA/Airflow, S3, Iceberg/Parquet, Athena/Trino, and PostgreSQL/Redshift, ensuring reliable, cost-efficient operations at the scale of a large portfolio of automated production jobs processing terabyte-to-petabyte data volumes. Successful candidates will be eligible to hold a U.S. Federal Public Trust security clearance (Moderate Risk). This position is contingent upon contract award.

Requirements

Bachelor's degree in computer science, Information Systems, Engineering, or related technical discipline. OR; In lieu of a degree, four additional years of related, specialized experience is required
Minimum of 4 years of experience in performance engineering, data engineering, or quality engineering for large-scale, data-centric systems.
Hands-on experience tuning Apache Spark/PySpark workloads and AWS Glue jobs.
Experience with workflow orchestration using Airflow/MWAA or similar tools.
Experience optimizing queries and storage across S3-based data lakes (Iceberg/Parquet), query engines (Athena or Trino), and relational databases (PostgreSQL, Redshift, or Oracle).
Foundational proficiency in Python and SQL.
Experience with load/performance testing and production troubleshooting of automated data pipelines at scale.
Strong analytical, root-cause analysis, and communication skills.
Ability to obtain and maintain a Moderate Risk Public Trust clearance; residing in the United States.

Nice To Haves

Experience with AWS cloud cost optimization.
Experience supporting operations across hundreds of concurrent scheduled pipelines.
Familiarity with CI/CD, Infrastructure-as-Code, and federal security and compliance requirements (FISMA, NIST 800-53, Zero Trust, Section 508, the Privacy Act of 1974).
Experience with AI-assisted development tools for debugging and performance tuning.
Experience with financial or regulatory datasets.
Willingness to support disaster recovery exercises and learn enterprise-level ETL best practice standards under senior guidance.

Responsibilities

Assist with Performance Tuning: collaborating with a senior engineer, assist in analyzing and tuning Spark/PySpark and AWS Glue job performance (including partitioning, clustering, batch sizing, and file format optimization such as Parquet, ORC, Iceberg).
Support Query Optimization: help optimize query performance across Athena, Trino, PostgreSQL, Redshift, and semantic-layer objects (e.g., tables, views, materialized views) contributing to the efficient execution of user queries, reports, and dashboards.
Collaborative Troubleshooting: assist in identifying, diagnosing, and resolving failed production jobs and performance bottlenecks to ensure data engineers can maintain data availability, integrity, and accuracy to comply with ingestion timelines and zero data-loss requirements.
Support Performance Testing: participate in periodic load and performance tests; assist in defining benchmarks, documenting/analyzing results, and drafting test reports with recommendations for system improvements.
Pipeline Monitoring: monitor pipeline health using CloudWatch, ETL metadata, log analysis, and dashboards; assist in hardening/optimizing error handling and automated job notifications.
Team Collaboration: coordinate with developers, testers, and stakeholders to resolve technical issues; participate actively in agile ceremonies and Program Increment planning events.
Production Operations Support: work as part of a team to support production operations across a large data pipeline portfolio, including (but not limited to) participating in a team on-call rotation for troubleshooting production issues and outages, defining and integrating performance and reliability requirements into ETL designs, shared code libraries, and enterprise ETL standards.