Integra ConnectRemote
Data Reliability Engineer- Oncology Analytics
United States
Full-time
1 week ago
$100,000 - $120,000 USD
H1B Sponsor Likely
Key skills
Data Reliability EngineeringETL/ELT toolsPythonSQLCloud platformsData validation frameworksData quality monitoringJavaScriptC#Power BITableauGitAnalytical skillsProblem-solving skillsAttention to detailCMachine LearningETLELTBISnowflakedbtAWSAzureMSSQLVersion Control
About this role
Integra Connect is a value-based, precision medicine company specializing in Health IT and digital health solutions. The Data Reliability Engineer will design and maintain data pipelines, implement automated testing, and ensure data integrity while collaborating with senior engineers and product teams to deliver trusted data products.
Responsibilities:
- Develop and maintain ETL/ELT pipelines using tools like dbt, MageAI, and ADF
- Implement test automation for data pipelines, including unit tests, integration tests, and data quality checks
- Collaborate with QA and DataOps teams to design validation frameworks leveraging metadata-driven approaches
- Profile and monitor data quality using tools like Data Profiling and Data Validation tests
- Work with cloud platforms (Azure or AWS) and data warehouses (Snowflake, MSSQL)
- Ensure compliance with data governance and security standards
- Partner with senior engineers to optimize performance and scalability
- Contribute to documentation and knowledge sharing for pipeline QA best practices
Requirements:
- Minimum of 4 years of experience as a Data Reliability Engineer
- Proficiency in Python and SQL; familiarity with JavaScript or C# is a plus
- Strong knowledge of relational databases and SQL optimization
- Experience with Snowflake and ADLS2
- Proficiency in ETL/ELT tools (dbt, MageAI, or ADF) and pipeline orchestration
- Understanding of cloud platforms (Azure or AWS)
- Familiarity with version control systems like Git
- Background in QA or test automation, with experience designing and implementing automated tests for data pipelines
- Strong analytical and problem-solving skills
- Attention to detail and commitment to data accuracy and compliance
- Experience with data validation frameworks and automated testing for pipelines
- Knowledge of metadata-driven QA and data quality monitoring
- Proficiency with Power BI or Tableau for data visualization
- Exposure to machine learning and data science principles
- Healthcare or oncology data experience (bonus, not required)