• Design, build, and maintain robust data pipelines (ETL/ELT) • Work with Databricks for large-scale data processing using Spark and Delta Lake • Optimize data workflows, performance, and data storage solutions • Collaborate with cross-functional teams including data analysts, engineers, and stakeholders • Ensure data quality, reliability, and scalability across systems • Contribute to continuous improvement of data architecture and processes

• Monitor and manage overnight scraper and ingestion runs, triaging failures and applying fixes in real time to minimize data gaps before US market open • Verify data completeness and quality across all automated feeds, flagging anomalies and coordinating with the Houston team on persistent issues • Maintain run logs, error documentation, and escalation notes for seamless async handoffs • Build and maintain scrapers, parsers, and ingestion pipelines across a growing set of energy market data domains • Contribute to the design and build-out of our broader ETL infrastructure, including scheduling, orchestration, and error handling • Write transformation logic to clean, normalize, and load raw data into PostgreSQL staging and production tables • Optimize existing pipelines for performance, reliability, and cost efficiency • Help build monitoring dashboards and alerting for pipeline health and data freshness • Document data lineage, schema changes, and pipeline dependencies

• Lead the technical architecture effort for our next generation cloud data platform • Partner with platform teams to design and deploy a cloud big data platform that is fit for purpose and in line with business goals and objectives • Contribute towards the definition and SDLC adoption of strategic enterprise platform architecture standards • Develop platform standards for how integrations are developed, and how features are developed within the ecosystem • Provide design and technical support for application teams that are re-architecting legacy/batch data solutions

• Design and develop scalable ETL/ELT solutions and data architectures (data lakes, data warehouses) • Optimize Snowflake queries and implement data governance best practices • Collaborate with stakeholders to translate business needs into technical solutions • Build APIs and integrate with email service providers and HCP data sources • Lead development efforts and coordinate with offshore teams • Conduct code reviews and ensure adherence to coding standards • Support CI/CD processes using tools like Terraform and Airflow • Maintain high standards of data quality and integrity across healthcare datasets.