Databricks Data Engineer

Job Description We are seeking a Databricks Data Engineer to join our growing team. In this role, you will build robust and scalable data pipelines on the Databricks Lakehouse Platform that support high‑quality analytics and machine learning solutions for our clients. You will play a critical role in designing workflows that ingest, transform, clean, normalize, and augment data from various sources - leveraging Databricks Delta Lake, Unity Catalog, and Spark for production‑grade pipelines. You should be comfortable working in cloud‑based environments - particularly Databricks - and have experience with structured and unstructured data. A strong command of SQL and Python is essential, along with hands‑on experience using Databricks (Delta Lake, Spark notebooks, Unity Catalog), Pandas, Apache Spark, or similar data transformation frameworks. Key Responsibilities Design and build reliable, scalable data pipelines for ingestion, transformation, normalization, and augmentation Work with structured, semi‑structured, and unstructured data across diverse environments Develop approaches to source data from diverse platforms (flat files, databases, APIs, streams, etc.) Develop and maintain data transformation workflows in Databricks using Delta Lake, Spark notebooks, and Unity Catalog Collaborate with cross‑functional teams to gather data requirements and translate them into actionable data models Perform data quality checks and implement validation logic to ensure reliable outputs Create basic visualizations to support validation, exploration, and stakeholder communication Optimize performance of pipelines in cloud and distributed computing environments Qualifications Required 3+ years of hands‑on production Databricks experience with SQL and Python in data engineering roles Experience with data transformation tools/frameworks such as DLT, dbt, and Apache Spark within the Databricks ecosystem Hands‑on experience with Databricks, including Delta Lake, Spark notebooks, and Unity Catalog in production environments Familiarity with cloud data platforms (e.g., Azure, AWS) Solid understanding of ETL/ELT processes and pipeline orchestration Experience with DataOps processes and tools such as Databricks Asset Bundles (DABs) and using version control systems like Git Strong communication and problem‑solving skills Proactive in seeking opportunities to learn and grow skillset Prior experience in a consulting or client‑facing role Preferred Advanced Databricks experience including Databricks Workflows/Jobs, Lakeflow Connect, Delta Live Tables (DLT), and performance tuning at scale Experience with modern Data and ML workflow tools (e.g., Airflow, MLflow) Familiarity with data visualization libraries or tools (e.g., matplotlib, Power BI, Tableau) Understanding of best practices in data modeling, data quality, and pipeline monitoring Additional Information Est. Salary Range (Colorado Only): $120,000-$140,000* *Disclaimer: In accordance with Colorado’s Equal Pay for Equal Work Act, effective January 1, 2021, a good faith hourly or base salary range must be posted for all positions where the work may be performed in the state of Colorado. Therefore, this good faith salary range will only apply where this described position will be performed in the state, and should not be considered the compensation range in other locations or for other positions. DevIQ Benefits Include Competitive financial compensation and utilization bonus plans Medical, Dental, Vision Insurance 401k, With 4% Matching Paid Time Off Health Savings Account (HSA)/Flexible Spending Account (FSA) Short‑Term/Long‑Term Disability Insurance Business funded Life Insurance Plan Dynamic yet relaxed work atmosphere Wide Variety of Growth Opportunities Compensation 120,000-$120,000 per year #J-18808-Ljbffr