Role Description This role is for a Technical Lead with ownership over the SAP Data Migration aspects of the BFS Data Engineering Team. The ideal candidate will have experience leading the technical aspects of the Data Migration team including: - Providing oversight and ownership over the technical architecture and end-to-end development process. - Implementing data migration solutions using SAP Data Services. - Ensuring timely delivery of high-quality, reliable, and cost-effective migration solutions from diverse ERP sources into SAP S/4 Hana and Azure Cloud. - Defining design guidelines using best practices related to SAP Data Services. - Coding/building pipelines, peer reviews, and general oversight. - Developing the cloud data platform as the environment matures. Qualifications - Bachelor's degree from an accredited college/university. - 7+ years relevant work experience or an equivalent combination of education and experience. - Experience leading ETL on multiple SAP data migration projects from end to end. - Demonstrated high involvement with SAP data object migration processes/tools and complex data extractions, transformations, and loading techniques. - Experience in SAP Data Migration Toolset: SAP Data Services (BODS), iDoc, BAPI, LSMW, RFC, DMC. - Experience in Azure data engineering toolset: Databricks, Microsoft SQL Databases (SQLMI), Azure DevOps. - Experience in basic data warehousing and modeling practices and techniques. - Operating System Technologies: Windows, Linux/Unix including VMs. - Database Technologies: Microsoft SQL, S/4 Hana, Sybase, ODBC/JDBC connection management. - Programming Languages: SQL, Python. Requirements - Manages and resolves data conversion issues during loading, upon consulting with functional team/client. - Demonstrated experience in performance tuning pipelines and applications related to the Data Migration process. - Demonstrated experience in IT security practices in data at rest and in motion. - Maintain Technical and Functional Documentation/Standards including Field Mapping, Validations, Process Flows, Relevancy Rules, etc. Benefits - Medical, dental, vision, and disability insurance plans. - 401(k) retirement savings plan. - PTO (including paid sick time). - 8 paid holidays per year (for salaried and hourly team members). Company Description Builders FirstSource is America’s largest supplier of building materials, value-added components, and building services to the professional market. We are committed to creating a diverse and inclusive workplace that welcomes candidates from all backgrounds and experience levels.

• Build and ship the systems behind Tern's AI features • Build the evaluation systems that answer whether an AI feature is good enough to ship and good enough to keep • Own data quality as a first-class concern • Build and maintain the ETL systems • Work alongside product squads to build reporting

• Own end-to-end data systems and pipelines, that other teams and customers rely on • Design and implement data integrations across multiple backend business systems, ensuring efficient and reliable data flows • Work on streaming data processing using frameworks like Apache Beam to handle real-time data ingestion and transformation • Build and maintain APIs to enable seamless data access and sharing across internal teams and platforms • Manage orchestration and automation of workflows using Airflow on Kubernetes • Define what "correct" means for the data you own, and back it with monitoring, alerting, and integration tests • Build reusable patterns and components (hooks, plugins, alerting utilities) that are easily adoptable by other engineers and processes • Break down ambiguous work into actionable tasks, surface edge cases and failure modes early, and clarify requirements with stakeholders • Communicate tradeoffs, assumptions, and risks clearly in design reviews and PRs

• Own the data platform strategy end-to-end — from ingestion architecture and scalable, multi-tenant data infrastructure to transformation pipelines, a modern BI layer, and how the platform grows as we add clients and data sources. • Drive the AI-on-data layer. Partner with our AI engineer to define how agents and LLMs access, query, and act on platform data — semantic models, retrieval patterns, and in-warehouse AI primitives. • Build and productize our integrations motion — ingesting data from a growing set of first- and third-party sources. Turn what today requires custom work into a repeatable, operable pattern. • Lead and develop our data engineering team. You'll manage directly, set technical direction, and raise the bar on quality — starting with a tight-knit team with room to grow. • Define the engineering standards for the data org — CI/CD, testing, infra-as-code, data lineage, governance, and observability — so the platform scales without fragility. • Be a strong hands-on presence on the warehouse and transformation layer — fluent enough in Snowflake to contribute meaningfully alongside the team, not just oversee it. • Partner with go-to-market teams to define what great looks like for client onboarding and data delivery, and drive engineering execution against that bar.