Senior Software Engineer in Test at ejkz

Setup: Hybrid
Location: Washington, District of Columbia · Oregon · +7
Level: not_specified

Description

PEMCO is seeking a Senior Software Engineer in Test (Sr. SDET) to ensure the quality, reliability, scalability, and performance of their enterprise data platforms, data pipelines, and analytics solutions. This role involves partnering with various internal teams to design and implement automated testing solutions, applying an engineering-first quality mindset, and focusing on data validation and CI/CD integration.

Required Skills

SQL
Python
PySpark
Java
Scala
JavaScript/TypeScript
GitHub Actions
Azure DevOps
Jenkins

Additional Information

Required Previous Experiences: 5+ years of experience in Quality Engineering, Software Testing, SDET, Test Automation, Data Testing, or related engineering roles.
3+ years of hands-on experience testing enterprise data platforms, data warehouses, data lakes, big data platforms, data pipelines, or analytics solutions.
3+ years of strong Property & Casualty insurance experience, including practical experience supporting or testing insurance data domains such as policy administration, underwriting, claims, billing, customer, actuarial, finance, compliance, or regulatory reporting.
Experience designing and implementing automated testing frameworks and reusable data validation utilities.
Experience with white-box testing, integration testing, data reconciliation, API testing, regression testing, performance testing, and root-cause analysis.
Experience working in Agile, DevOps, CI/CD, and cloud-based engineering environments.
Proven 5+ years of experience in testing big data & creating test frameworks & white box [testing].
Preferred Qualifications: Advanced SQL skills, including complex queries, joins, aggregations, reconciliation logic, and data validation patterns.
Hands-on experience with modern data platforms such as Databricks, Snowflake, Spark, Hadoop, Hive, Amazon EMR, BigQuery, SQL Server, Delta Lake, or similar technologies.
Experience with CI/CD tools such as GitHub Actions, Azure DevOps, Jenkins, or similar platforms.
Experience with source control, branching strategies, test automation repositories, and code review practices.
Understanding of distributed data processing, data modeling, ETL/ELT patterns, data lineage, metadata, and data quality controls.
Experience with insurance data warehouse modernization, cloud migration, data governance, analytics enablement, or AI/ML data quality initiatives.
Experience creating self-service test data tools, reusable validation libraries, or automated quality dashboards.
Experience with AI-enabled testing, GitHub Copilot, test generation tools, or intelligent automation capabilities.
Certifications or coursework in software testing, quality engineering, cloud data platforms, data engineering, or property and casualty insurance.
Quality Engineering Mindset: Builds quality into solutions through automation, prevention-focused practices, and engineering discipline.
Insurance Business Acumen: Understands property and casualty insurance workflows, data relationships, operational risks, and business impact.
Analytical Problem Solving: Diagnoses complex data issues, identifies root causes, and develops durable solutions.