Software Development Engineer in Test (SDET)
New
M
Massive RocketMartech and data
Anywhere in EuropeContract
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLJiraAirflowRESTful APIsdbtDatabricks
Requirements
- Mastery of SQL for complex data validation and identifying anomalies across large record sets.
- Proficiency in Python for building automated test suites and interacting with APIs.
- Experience establishing data test automation frameworks from scratch.
- Hands-on experience testing within Databricks or an equivalent cloud lakehouse or warehouse; understanding of Delta Lake or similar architectures.
- Experience validating data transformations across near-real-time, streaming, and batch pipelines.
- Familiarity with orchestration tools such as Airflow or dbt.
- Experience validating data flows through a Customer Data Platform, particularly mParticle, including event ingestion, identity resolution, and audience syncs.
- Experience triaging data anomalies and tracking pipeline failures in Jira.
- Experience testing REST APIs and validating data payloads between systems.
- Bachelor’s degree in Computer Science, Data Engineering, or a related technical field.
- Familiarity with Braze Data Track API or Cloud Data Ingestion (CDI) is a bonus.
- Experience testing privacy compliance and consent frameworks such as OneTrust is a bonus.
- Experience embedding data quality checks into CI/CD pipelines such as GitHub Actions or GitLab CI is a bonus.
Responsibilities
- Design automated validation frameworks for data contracts, schema compliance, and identity resolution in Databricks.
- Build and maintain automated UI and behavioral tests that simulate customer journeys across web and app.
- Verify behavioral events, mParticle tags, and OneTrust consent tokens at the application layer.
- Validate data flows across Databricks, mParticle, Braze, and OneTrust.
- Write integration scripts and mock API payloads to test cross-platform actions and user activation or suppression.
- Run end-to-end tests for POS, web, app, and CRM data collection pipelines.
- Validate data freshness and latency against near-real-time SLAs.
- Maintain automated data validation and hygiene rules to detect corrupted records and schema drift.
- Audit data flows for consent and preference management in line with GDPR and UK GDPR.
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