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Databricks Engineer

ShaarproAustin, TX🇺🇸United StatesPosted 25 Jul 2026

Why This Role Stands Out

This role offers significant autonomy to design and build enterprise-grade data solutions on Databricks, directly impacting business objectives. You will thrive here if you are an experienced engineer with a passion for scalable architectures and translating complex requirements into high-performance analytics, with the flexibility of a hybrid work environment. Embrace this opportunity to shape innovative data strategies and advance your career.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

We are seeking a Senior Databricks Engineer with 8+ years of experience to design, build, and optimize enterprise-grade data solutions on Databricks. In this role, you will work with broad latitude and independence, translating complex business objectives into scalable, cost-effective data architecture. You will bridge the gap between technical requirements and business needs—conducting feasibility studies, analyzing user workflows, and delivering high-performance lakehouse analytics.

Key Responsibilities

  • Pipeline & Lakehouse Architecture: Design, build, and maintain scalable ETL/ELT ingestion pipelines utilizing Lakeflow Declarative Pipelines (DLT), PySpark/Scala, and the Medallion Architecture (Bronze, Silver, Gold).

  • Business Analysis & Data Modeling: Collaborate with stakeholders to capture requirements, perform cost/benefit analyses, and build robust dimensional models (Star/Snowflake schemas).

  • Analytics & Visualization: Develop dynamic native Databricks SQL dashboards, Databricks Apps, and custom analytical solutions to surface actionable insights.

  • Governance & Operations: Implement data quality, security, and governance frameworks. Optimize workload performance, monitor compute efficiency, and manage pipeline orchestration via Lakeflow Jobs or Airflow.

Candidate Qualifications

Required Experience (8+ Years)

  • Databricks & Spark: Hands-on experience architecting and tuning ETL/ELT data pipelines on Databricks using Apache Spark (PySpark or Scala).

  • Lakehouse Stack: Deep knowledge of Delta Lake, Medallion architecture, and Lakeflow Declarative Pipelines (DLT).

  • Data Modeling & SQL: Strong proficiency in SQL and dimensional data modeling (Star/Snowflake schemas).

  • Analytics & Governance: Experience developing native Databricks dashboards/apps and establishing data security, quality, and governance practices.

  • Orchestration: Experience scheduling and managing offline jobs using Lakeflow Jobs (Databricks Workflows) or similar tools (e.g., Airflow).

  • Communication: Exceptional verbal and written communication skills with a proven ability to translate complex data concepts for business leadership.

Preferred Qualifications

  • Active Databricks Certification (Data Engineer Associate or Professional).

  • Experience with CI/CD practices for data pipelines (Git-based workflows, DevOps).

  • Prior experience in public sector or state government environments.

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