Test Lead

Platform Strategy and Governance

• Define a federated test strategy, standards, and risk tiers with corresponding quality gates.
• Establish test taxonomies (e.g., functional, data quality, performance, reliability, security) and align them to domain SLOs.
• Implement policy-as-code governance to balance team autonomy with guardrails.

Testing Platform Architecture

• Lead the design and delivery of the testing platform, including reusable test frameworks, test data services, and observability/reporting tools.
• Provide SDKs/libraries and DSLs to simplify and standardize test authoring in Python/Java.
• Integrate with schema registries and enforce data contract compatibility (backward/forward).
• Build resilience testing harnesses for pipelines and services (e.g., fault injection, replay/backfill).

Patterns, Templates, and Enablement

• Create reusable CI/CD templates with quality gates and blueprints for common use cases (e.g., dbt model testing, Spark pipelines, Kafka streams, REST APIs).
• Publish reference implementations and sample repositories to demonstrate unit, integration, end-to-end, performance, and resilience testing.
• Partner with vertical teams to bootstrap testing for priority products and establish shift-left practices (e.g., pre-commit tests, PR checks).

Test Data and Environment Management

• Deliver solutions for synthetic data generation, masking, subsetting, and versioned golden datasets.
• Provide ephemeral environments and dependency virtualization for faster, deterministic testing.
• Monitor data drift and define schema evolution and rollback strategies.

Observability and Reporting

• Instrument tests with OpenTelemetry and centralize reporting via dashboards (e.g., test coverage, flakiness, trend analysis).
• Ensure traceability from requirements to test results for auditability and compliance.
• Deliver release readiness packs and quality scorecards for stakeholders.

Team Leadership and Collaboration

• Manage and guide offshore engineers, ensuring adherence to coding standards and delivery timelines.
• Collaborate with data engineers, developers, SREs, product owners, and governance teams to align quality practices.
• Drive continuous improvement in testing (e.g., flakiness reduction, performance optimization, cost-aware testing).

Key Outcomes/Success Criteria

• A self-service testing platform adopted by vertical teams, featuring reusable test frameworks, CI/CD templates, and test data services.
• Reference blueprints for testing common archetypes and use cases.
• Centralized dashboards and evidence reports for test results and quality metrics.
• Onboarding of priority vertical teams to the platform, supported by training and enablement.
• Measurable quality improvements, such as reduced escaped defects, faster release readiness, and consistent quality gate enforcement.

Do you have experience in Virtualization?, * 10+ years in software quality engineering/test automation, with 3-5 years building testing platforms or developer enablement tools.

• Expertise in data platform testing (e.g., data quality, pipeline validation, contracts) across warehouses, lakes, and streaming systems.
• Strong hands-on experience with Python or Java, test frameworks (e.g., pytest, JUnit/TestNG), and CI/CD pipelines.
• Proven experience driving federated quality practices and collaborating with distributed teams.

Preferred Qualifications

• Data Testing: Great Expectations, Soda, Deequ, dbt tests, and anomaly detection.
• API/Contract Testing: REST Assured, Pact, schema registry tools (Avro, Protobuf, JSON Schema).
• Performance/Reliability Testing: k6, JMeter, Locust, chaos testing tools.
• Data Platforms: Snowflake, Spark, Kafka/Kinesis, dbt, Airflow/Dagster.
• Cloud/DevOps: AWS, Docker/Kubernetes, Terraform, CI/CD platforms.
• Observability: OpenTelemetry, Prometheus, Grafana.