Senior Software Engineer in Test (Sr. SDET)

PEMCO•Seattle, WA

1d•$85,559 - $161,580•Remote

About The Position

PEMCO has an opportunity for a Senior Software Engineer in Test (Sr. SDET) to join our community. This position is responsible for ensuring the quality, reliability, scalability, and performance of PEMCO's enterprise data platforms, data pipelines, and analytics solutions. This role partners closely with Data Engineering, Data Governance, Analytics, AI, Product, and Technology teams to design and implement automated testing solutions across data lakes, data warehouses, cloud data platforms, and reporting environments. This role goes beyond traditional test execution. The Sr. SDET will apply an engineering-first quality mindset by designing reusable test automation frameworks, developing data validation utilities, integrating testing into CI/CD pipelines, and using white-box testing techniques to validate complex data transformations, business rules, data lineage, integration logic, and performance quality before issues impact production. Strong Property & Casualty insurance experience is required. The successful candidate must be able to understand and test insurance data domains such as policy administration, underwriting, claims, billing, customer, actuarial, finance, regulatory reporting, and related operational data flows.

Requirements

B.A./B.S. degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science, Data Engineering, or related field or equivalent experience required.
Bachelor’s degree in Computer Science, Information Technology, Software Engineering, Data Engineering, or related field, or equivalent combination of education and experience required.
5+ years of experience in Quality Engineering, Software Testing, SDET, Test Automation, Data Testing, or related engineering roles required.
3+ years of hands-on experience testing enterprise data platforms, data warehouses, data lakes, big data platforms, data pipelines, or analytics solutions required.
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 required.
Experience designing and implementing automated testing frameworks and reusable data validation utilities required.
Experience with white-box testing, integration testing, data reconciliation, API testing, regression testing, performance testing, and root-cause analysis required.
Experience working in Agile, DevOps, CI/CD, and cloud-based engineering environments required.
Proven 5+ years of experience in testing big data & creating test frameworks & white box testing.
Advanced SQL skills, including complex queries, joins, aggregations, reconciliation logic, and data validation patterns.
Programming experience with Python, PySpark, Java, Scala, JavaScript/TypeScript, or comparable languages.
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.
Collaboration & Communication: Explains technical concepts clearly and partners effectively across technology and business teams.
Continuous Improvement: Identifies opportunities to improve automation, reliability, delivery speed, and quality outcomes.
Responsible AI Enablement: Uses AI-assisted tools in a secure, ethical, and compliant manner consistent with PEMCO standards.

Responsibilities

Partner with business and technology teams to understand requirements and contribute to solution design for analytics and AI/ML initiatives.
Design, develop, and execute comprehensive test strategies for enterprise data platforms, data pipelines, analytics solutions, and cloud-based data environments.
Apply white-box testing techniques to validate data transformation logic, orchestration processes, source-to-target mappings, business rules, and integration pathways.
Define test coverage expectations, data quality gates, release readiness criteria, and automated validation standards across the software delivery lifecycle.
Partner with engineering teams to shift quality practices earlier in design, development, code review, and deployment processes.
Develop and maintain traceability between business requirements, insurance data rules, technical design, and automated test coverage.
Build automated validation processes to verify data accuracy, completeness, consistency, timeliness, reconciliation, and integrity across source and target systems.
Validate large-scale datasets and distributed processing jobs across platforms such as Databricks, Snowflake, Spark, Hadoop, Hive, Amazon EMR, BigQuery, or similar technologies.
Develop reusable utilities for data comparison, schema validation, metadata validation, row-count reconciliation, data profiling, and anomaly detection.
Investigate production defects, data anomalies, failed pipelines, and quality exceptions to identify root causes and recommend durable corrective actions.
Partner with Data Governance and business teams to validate data definitions, lineage, standards, and control requirements.
Design, build, and maintain scalable automated testing frameworks for ETL, ELT, API, integration, regression, performance, and end-to-end testing.
Integrate automated tests into CI/CD pipelines using GitHub Actions, Azure DevOps, Jenkins, or comparable tools.
Develop automated quality reporting, test metrics, and dashboards that provide actionable insight into test coverage, defect trends, and platform readiness.
Leverage AI-assisted development and test automation tools responsibly to improve test creation, coverage, maintainability, and delivery velocity.
Continuously improve automation reliability by reducing flaky tests, improving test data management, and strengthening repeatability across environments.
Conduct performance, scalability, and reliability testing for data processing workloads, pipelines, and analytics solutions.
Evaluate system behavior under varying data volumes, schedules, concurrency patterns, and processing windows.
Identify bottlenecks, latency issues, data quality risks, and edge cases that may impact downstream reporting, analytics, operational processes, or customer outcomes.
Collaborate with engineers and architects to improve pipeline reliability, observability, monitoring, and recovery processes.
Validate insurance business processes, calculations, data structures, and data flows supporting policy, underwriting, claims, billing, customer, actuarial, finance, compliance, and regulatory reporting functions.
Translate insurance business requirements and data rules into effective test scenarios, automated validations, and release quality criteria.
Identify risks related to insurance data quality, downstream operational impact, reporting accuracy, auditability, and regulatory obligations.
Partner with business stakeholders and technology teams to ensure testing reflects the realities of property and casualty insurance operations.
Participate in design reviews, architecture discussions, sprint planning, defect triage, release readiness, and post-implementation reviews.
Partner with Data Engineers, Software Engineers, Architects, Product Managers, Business Analysts, and business stakeholders to align quality practices with business priorities.
Mentor team members on SDET practices, data validation approaches, automation design patterns, and quality engineering standards.
Communicate risks, issues, test results, and recommendations clearly to technical and non-technical audiences.
Demonstrate behaviors consistent with PEMCO's policies, values, code of ethics, and business conduct.
Other duties as assigned.

Benefits

Medical, dental, and vision plans for employees and eligible family members with generous employer premium cost shares.
Employer-paid basic life and accidental death & dismemberment insurance policies.
Long- and short-term disability benefit coverages.
401(k) plan with a generous employer match (2 for 1 on the first 6% employee pre-tax and/or Roth deferral, up to federal maximums).
Vacation time.
Eight (8) paid holidays.
Four (4) floating holidays.
Up to ten (10) days of sick leave immediately upon hire (pro-rated based on hire date and full-time/part-time status).
Paid time off for bereavement.
Paid time off for jury duty.
Paid time off for employee volunteering in the community.
Education Assistance Program after one year of service.
Scholarship program for children of PEMCO employees after one year of service.
Children’s birthday gift program.
Flexible Spending Accounts.
Employee Assistance Program.
Charitable gift matching.
Discretionary bonuses.
Tiered sales commissions and/or incentives.