Associate Performance Engineer

eSimplicity

Associate Performance Engineer supporting cloud-based enterprise data platform for a federal financial regulatory agency. Collaborating on performance tuning, query optimization, and troubleshooting in a hybrid environment.

Posted 7/17/2026full-timeColumbia • Maryland • 🇺🇸 United StatesJuniorMid-Level💰 $93,000 - $136,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in performance tuning and optimization of data pipelines using Spark/PySpark and AWS Glue, along with strong analytical skills for troubleshooting and enhancing query performance across various data storage and processing technologies.

Highest-signal resume keywords

Performance EngineeringData EngineeringApache Spark/PySpark TuningAWS Glue Job OptimizationQuery Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Performance TuningData Pipeline MonitoringLoad TestingSQLPython

Soft Skills

Analytical SkillsCommunication SkillsRoot-Cause Analysis

Tools & Technologies

AWS GlueApache SparkAirflowAthenaTrinoPostgreSQLRedshiftS3CloudWatch

Certifications & Qualifications

Moderate Risk Public Trust Clearance

Industry Keywords

Data-Centric SystemsETLData LakesPerformance TestingAgile Methodologies

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSETLOraclePostgresPySparkPythonSparkSQL

About the role

Key responsibilities & impact

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 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
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

Requirements

What you’ll need

Bachelor's degree in computer science, Information Systems, Engineering, or related technical discipline
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

Benefits

Comp & perks

medical, dental, and vision coverage
401(k) retirement benefits
paid time off
paid holidays
life and disability insurance
additional wellness and employee support programs