Principal Databricks Architect

Bounteous is a global AI Services firm where agentic engineering and human experience converge to deliver transformative business outcomes for the enterprise. We help organizations design, build, and scale AI-driven products, platforms, and processes. With more than 5,000 team members worldwide, Bounteous delivers AI that sticks, powering adoption and outcomes that move organizations from experimentation to true transformation. Bounteous is backed by New Mountain Capital, a New York-based growth-oriented investment firm that emphasizes business building. We are seeking a Lead Databricks Engineer/Architect to design, build, and scale our cloud-based lakehouse platform. In this role, you will own the end-to-end architecture of our data ecosystem on Databricks, partner with data science and analytics teams to productionize ML and analytical workloads, and set the technical direction for ingestion, transformation, governance, and performance optimization across petabyte-scale datasets. You will be a hands-on technical leader: writing production code, mentoring engineers, and shaping standards that the broader data organization will adopt. Information Security Responsibilities Promote and enforce awareness of key information security practices, including acceptable use of information assets, malware protection, and password security protocols Identify, assess, and report securit [... source excerpt omitted ...] ivacy and protection standards (GDPR, CCPA, etc.) Ensure data protection measures are integrated throughout the information lifecycle to safeguard sensitive information Role and Responsibilities Architect and lead the implementation of an enterprise lakehouse on Databricks (Delta Lake, Unity Catalog, Photon, Workflows) across one or more major clouds (AWS, Azure, or GCP). Design scalable batch and streaming data pipelines using PySpark, Spark SQL, Structured Streaming, and Delta Live Tables; establish patterns for ingestion from operational systems, event streams, and third-party APIs. Define and enforce platform standards for data modeling (medallion architecture), CI/CD, code q [... source excerpt omitted ...] Engage with stakeholders across analytics, product, and finance to translate business needs into a roadmap for the data platform. Ability to travel around once a month Required Qualifications 10+ years of data engineering experience, with 4+ years building production workloads on Databricks. Deep expertise in Apache Spark (PySpark and Spark SQL) — including performance tuning, partitioning strategy, and the Catalyst/Photon execution model. Strong hands-on experience with Delta Lake, Unity Catalog, Databricks Workflows, and Delta Live Tables. Production experience on at least one major cloud (AWS, Azure, or GCP), including networking, IAM, storage (S3/ADLS/GCS), and compute primi