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Senior Databricks Data Engineer

MaddisoftAustin, TX🇺🇸United StatesPosted 26 Jul 2026

Why This Role Stands Out

This role offers significant opportunities to leverage your Databricks and Spark expertise to design and implement enterprise-level data solutions, driving impactful business decisions. You'll thrive here if you are a motivated, independent professional adept at analyzing requirements and collaborating with stakeholders to deliver scalable, analytics-ready datasets. Don't miss this chance to grow your career with a reputable company.

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

job Title: Senior Databricks Data Engineer

Location: Austin, TX (Hybrid)

Interview Mode: In-Person

Job Summary

We are seeking an experienced Senior Databricks Data Engineer with 8+ years of IT experience in designing, developing, and delivering enterprise data solutions. The ideal candidate will have extensive expertise in Databricks, Apache Spark, Python/Scala, SQL, and modern data lakehouse architectures. This role requires a highly motivated professional who can independently analyze business requirements, design scalable data solutions, optimize data pipelines, and deliver analytics-ready datasets that support business decision-making.

The candidate should be capable of planning and executing complex technical tasks with minimal supervision while collaborating effectively with business and technical stakeholders.

Key Responsibilities

  • Analyze business requirements and translate them into scalable data engineering solutions.
  • Design, develop, and optimize ETL/ELT pipelines using Databricks and Apache Spark (PySpark or Scala).
  • Build and maintain Lakehouse architectures using Delta Lake and Medallion Architecture (Bronze, Silver, Gold).
  • Develop and manage Lakeflow Declarative Pipelines (formerly Delta Live Tables) and orchestrate workflows using Lakeflow Jobs or similar scheduling tools.
  • Design and implement dimensional data models, including Star and Snowflake schemas, to support enterprise reporting and analytics.
  • Create Databricks SQL dashboards, Databricks Apps, and other analytical solutions that provide actionable business insights.
  • Implement data governance, security, validation, and data quality frameworks to ensure reliable and trusted data.
  • Optimize workload performance, scalability, monitoring, and operational efficiency while managing infrastructure costs.
  • Perform system analysis, evaluate alternative technical solutions, and conduct cost-benefit analyses to recommend optimal approaches.
  • Collaborate with cross-functional teams to gather requirements, document technical specifications, and deliver high-quality data solutions.
  • Support CI/CD implementation for data engineering projects using Git-based workflows and DevOps best practices.
  • Communicate technical concepts and project updates effectively to both technical and non-technical stakeholders.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent experience).
  • 8+ years of experience designing, developing, deploying, or supporting enterprise technology solutions.
  • 8+ years of hands-on experience with Databricks and Apache Spark for building and optimizing ETL/ELT pipelines.
  • Strong expertise in SQL and Python (or Scala) for large-scale distributed data processing.
  • Experience with Delta Lake, Lakehouse architecture, and Medallion Architecture (Bronze, Silver, Gold).
  • Experience implementing Lakeflow Declarative Pipelines (DLT) and scheduling jobs using Lakeflow Jobs or similar orchestration platforms.
  • Strong experience in data warehousing concepts and dimensional data modeling (Star/Snowflake schemas).
  • Experience developing dashboards and applications within Databricks using Databricks SQL and Databricks Apps.
  • Strong understanding of data governance, data quality, data security, and enterprise data management best practices.
  • Experience with CI/CD pipelines, Git, and DevOps practices for data engineering.
  • Excellent analytical, problem-solving, verbal, and written communication skills.
  • Ability to work independently while managing multiple complex initiatives.

Preferred Qualifications

  • Experience working in public sector or government environments.
  • Databricks Certified Data Engineer Associate or Professional certification.
  • Experience with workflow orchestration tools such as Apache Airflow or similar platforms.
  • Familiarity with cloud-based data platforms and modern data engineering best practices.

Skills

SQL
Scala
ETL
Snowflake
Airflow
Apache
Apache Spark
Databricks
Git
Python

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