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Tech Stack
Tools & technologiesApacheAWSAzureCloudGoogle Cloud PlatformPySparkPythonScalaSparkSQLTerraformUnity
About the role
Key responsibilities & impact- 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 quality, testing, observability, and cost optimization.
- Lead the governance strategy using Unity Catalog — fine-grained access control, data lineage, audit, and PII handling — in partnership with security and compliance.
- Optimize Spark workloads for performance and cost: cluster sizing, Photon, autoscaling, file layout, Z-ordering, caching, and query tuning.
- Partner with ML engineers and data scientists to operationalize models using MLflow, feature stores, and model serving on Databricks.
- Own the cloud infrastructure footprint for the platform: networking, IAM, secrets, encryption, and Terraform/IaC for Databricks workspaces and supporting services.
- Mentor a team of data engineers; lead architecture reviews, code reviews, and technical design sessions; raise the bar on engineering practices.
- Engage with stakeholders across analytics, product, and finance to translate business needs into a roadmap for the data platform.
Requirements
What you’ll need- 8+ 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 primitives.
- Proficiency in Python and SQL; comfort with Scala is a plus.
- Experience designing medallion (bronze/silver/gold) architectures and dimensional models for analytics.
- Strong CI/CD and DevOps practice: Git, Terraform, Databricks Asset Bundles or dbx, automated testing of data pipelines.
- Track record of leading technical projects end-to-end and mentoring engineers.
- Excellent written and verbal communication; able to drive alignment with both engineering and business stakeholders.
Benefits
Comp & perks- Bounteous is willing to sponsor eligible candidates for employment visas.
- Accommodation will be provided at any point throughout the hiring process for candidates with accommodation needs.
- We welcome applications from all qualified candidates.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
DatabricksDelta LakePySparkSpark SQLStructured StreamingDelta Live TablesCI/CDDevOpsPythonSQL
Soft Skills
mentoringcommunicationstakeholder engagementleadershiptechnical design
