Databricks Data Engineer
Skills
About the role
Company Description
DevIQ specializes in building modern cloud and data solutions – and we believe in the power of software and technology to improve lives. Join us to partner with passionate mid-market companies focused on reducing energy costs, curing disease, improving education, building smart cities, and more. From true innovation and synergetic cloud & technology partnerships to competitive full-time benefits and a strong team culture, DevIQ is a great place to work.
At DevIQ, you’ll:
Build your career with a supportive, inclusive team that appreciates people, creates value, embraces growth, and “owns the problem” as a team.
Enjoy opportunities to learn, exposure to new industries, and building end-to-end solutions through meaningful work on active client projects.
Work remotely and/or from our modern studio in downtown Denver.
Bring your unique perspective and experience to multi-disciplinary teams.
Collaborate on and contribute to transformative digital experiences that touch millions of lives, watching your work make an impact.
Please note that you must be a U.S. citizen or eligible to work in the U.S. to be considered for this role, and third-party candidates will not be accepted.
Job Description
We are seeking a Databricks Data Engineer to join our growing team. In this role, you’ll build robust and scalable data pipelines on the Databricks Lakehouse Platform that support high-quality analytics and machine learning solutions for our clients. You’ll 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
This Data Engineer role pays $120k-$140k/yr. Within typical range for data engineer roles in United States.
Questions about this role
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