• Build and maintain ingestion pipelines (Python-based ETL/ELT) • Design structured transformation workflows using dbt, SQLMesh, or equivalent • Convert unstructured transcripts and documents into normalized database records • Maintain PostgreSQL architecture (structured tables, JSONB, indexing strategy) • Develop attribute extraction frameworks for technical, commercial, and risk signals • Ensure data quality, consistency, and lineage from raw interaction to structured output • Collaborate with AI/ML engineers to ensure clean model inputs

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This position involves significant impact on our data analytics systems by building and maintaining frameworks that ensure reliable data acquisition, validation, and loading. - Build and maintain production quality data pipelines between operational systems and BigQuery. - Implement data quality checks and monitoring processes for data accuracy. - Contribute to our ingestion framework utilizing various data load tool connectors. - Create and maintain comprehensive documentation for engineering processes. - Monitor and ensure observability of internal data pipelines. - Troubleshoot and resolve data pipeline issues. - Align source and staging layers in dbt systems to efficiency and availability standards. - Investigate and implement event-driven data movements and transformations. - Explore and implement analytic data storage formats. Qualifications - Software development skills in Python, Java, Scala, or Go. - High proficiency in SQL. - Experience with data ingestion pipelines and workflow orchestration systems. - Knowledge of dbt or similar data transformation tools. - Highly motivated self-starter with problem-solving abilities. - Excellent communication skills for cross-functional collaboration. Benefits - Fully remote work with a global culture. - Career growth pathways and defined development opportunities. - Open communication and transparency within teams. - Autonomy to innovate and contribute meaningfully. - In-person onboarding for new hires. - Global annual leave policy with 30 days off and dedicated shutdown days.

• Support the operations of the Medicaid Enterprise Data Warehouse (EDW). • Work with Medicaid program stakeholders, technical teams, and data architects to translate complex business requirements into detailed functional specifications. • Lead the elicitation, documentation, and validation of business requirements for Medicaid data warehouse initiatives. • Translate Medicaid program requirements into functional specifications for ETL processes, data models, and reporting solutions. • Analyze Medicaid data from various source systems including Claims processing systems, Provider enrollment systems, and Member eligibility systems. • Collaborate with data architects and ETL developers to define source-to-target mappings and data transformation rules. • Develop test scenarios and support system integration testing (SIT) and user acceptance testing (UAT).

• Build and optimize data systems that power batch processing, real-time streaming, pipeline orchestration, data lake management, and data cataloging. • Use expertise in solving big data problems and apply design thinking, coding and analytical skills to develop data pipelines that support marketing data products. • Integrate services directly with Lending Club’s products and with external vendors. • Work with modern data technologies such as Hadoop, Spark, DBT, Dagster/Airflow, Atlan, Trino, etc., and cloud technologies across AWS stack. • Identify, design, and implement automation of manual processes, optimizing data delivery, reducing Cloud cost, etc. • Implement processes and systems to monitor Data Quality, Observability, Governance and Lineage. • Support operations to manage the production environment and help in resolving production issues with RCA. • Write unit/integration tests, adopt Test-driven development, contribute to engineering wiki, and document design/implementation etc.