Senior Data Engineer – Databricks | Azure | Data Engineering

This is remote for US applicants only.

Role Overview

As a Senior Databricks Data Engineer, you will work directly with enterprise customers to design, develop, and implement modern cloud data solutions. You'll translate business requirements into scalable technical solutions, build high-performance data ingestion pipelines, and lead end-to-end delivery across multiple client engagements.

You'll collaborate with architects, business stakeholders, AI engineers, analytics teams, and cloud platform specialists to deliver production-ready data platforms that power reporting, analytics, machine learning, and AI applications.

Key Responsibilities

• Translate business requirements into scalable technical specifications and implementation plans.
• Design, build, and optimize enterprise data ingestion pipelines.
• Develop scalable ETL/ELT frameworks using Azure and Databricks.
• Build reliable batch and streaming data pipelines.
• Lead end-to-end implementation of enterprise data engineering projects.
• Develop reusable frameworks, accelerators, and automation components.
• Optimize data quality, performance, scalability, and cost.
• Collaborate with solution architects, product owners, and business stakeholders.
• Implement CI/CD and DevOps best practices for data engineering.
• Support production deployments and troubleshoot complex data issues.
• Mentor junior engineers and participate in architecture and design reviews.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field.
• 5+ years of hands-on experience in Data Engineering.
• 5+ years building enterprise data ingestion and integration solutions.
• Strong experience with Databricks and Apache Spark.
• Strong Scala programming experience.
• Hands-on experience with Azure Data Factory (ADF).
• Strong SQL development skills.
• 5+ years working with Microsoft SQL Server.
• Experience designing enterprise data models and data warehouses.
• Experience developing REST API integrations and working with structured and semi-structured data.
• Strong troubleshooting and performance tuning skills.

Preferred Qualifications

• Delta Lake
• Unity Catalog
• Azure Data Lake Storage
• Azure DevOps
• GitHub Actions
• Databricks Certifications

What Success Looks Like

• Deliver enterprise-grade cloud data platforms on time and within budget.
• Build scalable, high-quality data pipelines with strong reliability on Databricks
• Enable trusted, AI-ready data for enterprise customers.
• Contribute reusable frameworks that accelerate future implementations.
• Act as a trusted technical advisor to customers and internal teams.