Senior Databricks Data Engineer

Senior Databricks Data Engineer

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

We are looking for an experienced Senior Databricks Data Engineer to help modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers. This role also uses AI tools like Claude and GitHub Copilot to speed up development.

What you will do:

• Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.
• Model and maintain a medallion (bronze/silver/gold) architecture serving analytics, reporting, and machine learning consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal business disruption.
• Use Claude or Github Copilot as a development accelerator, generating code scaffolding, writing and reviewing tests, creating documentation and prototyping solutions.
• Write clean, well-tested Python and SQL; maintain high standards through code review and documentation.
• Optimize Spark jobs and Delta tables for performance and cost, including partitioning, clustering, caching, and cluster sizing.
• Implement data quality, lineage, and governance controls using Unity Catalog and automated validation checks.
• Debug, troubleshoot, and resolve pipeline failures, data defects, and production incidents.
• Participate in Agile or product-centric delivery practices including sprint planning and retrospectives.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance best practices.

MUST HAVES:

• 4+ years of professional experience in data engineering, featuring direct expertise with Apache Spark and cloud-based data architectures.
• Strong hands-on experience building data pipelines with Databricks, Apache Spark (PySpark), and Delta Lake.
• Advanced SQL and Python, with strong data modeling skills across dimensional and Lakehouse patterns.
• Experience with streaming ingestion using Structured Streaming, Auto Loader, Kafka, or Event Hubs.
• Experience with workflow orchestration (Databricks Workflows, Airflow, or Azure Data Factory).
• Experience with legacy platform migrations, ETL modernization, or managing data hygiene when porting old systems.
• Strong problem-solving, collaboration, and communication skills, including mentoring junior engineers and explaining data concepts to non-technical stakeholders.
• Familiarity with Unity Catalog, data governance, access control, and PII handling.
• Experience with dbt or an equivalent transformation framework.
• Familiarity with secure coding standards and industry security best practices.
• Experience delivering production data platforms at scale.
• Upper-intermediate English level.

NICE TO HAVES:

• Experience with Infrastructure as Code (IaC) using Terraform and CI/CD using Azure Devops.
• Experience working with relational databases (specifically PostgreSQL) and data persistence concepts.
• Familiarity with logging and monitoring tools (e.g., Dynatrace, CloudWatch, Databricks system tables).
• Experience working in Agile or team-based development environments preferred.

Perks and benefits:

• Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget.
• Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews.
• Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm.
• Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands.
• Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized.
• Well-being & support: access local well-being programs and people-focused support tailored to your location.

Meet our recruitment process:

1. Application → Coding Challenge → Video Interview → Technical Interview or Hiring Manager Interview
2. Each step helps us understand your skills and overall fit. If it's a match, you'll receive an offer.