Senior Data Engineer (Databricks)

Sparq is a modern product engineering partner that helps organizations modernize confidently in the age of AI. The Senior Data Engineer will build and migrate large-scale data pipelines into Databricks, develop production-grade solutions, and collaborate with various stakeholders to enhance data reliability and performance.

Responsibilities:

• Build and migrate large-scale batch data pipelines from legacy data platforms into Databricks
• Develop and optimize production-grade solutions using Python, Spark, and advanced SQL
• Support parallel legacy and cloud data environments throughout the migration and validation process
• Serve as a subject matter expert while remaining hands-on with day-to-day development and troubleshooting
• Actively use AI tools, including Claude through our Anthropic partnership, to streamline tasks, improve the quality of your work, and share best practices with teammates while continuously seeking new ways to integrate AI into your everyday workflows
• Lead technical design conversations and guide implementation within an established architecture and project framework
• Collaborate with developers, architects, and business stakeholders to communicate technical decisions, risks, and progress
• Improve pipeline reliability and performance through testing, monitoring, tuning, and production support
• Use GitHub Copilot when helpful to support development productivity
• Participate in a rotating on-call schedule approximately every four to six weeks

Requirements:

• Recent hands-on experience building production batch solutions in Databricks, ideally within the past 12–18 months
• Strong development experience with Python and Apache Spark
• Advanced SQL skills, including complex query development and performance tuning
• Consultative approach and problem solving skills to successfully align digital solutions with long-term business goals of the client
• Experience delivering large-scale migrations from legacy data platforms to cloud-based environments, preferably involving Teradata or a comparable platform
• Experience supporting legacy and cloud systems operating in parallel during a migration
• The ability to lead design and technical-direction discussions while remaining actively involved in coding and implementation
• Hands-on experience using AI tools to enhance daily work, or a strong desire to do so, including a willingness to experiment, learn, and champion AI adoption within your role
• Strong communication skills across technical teams, architects, business partners, and leadership
• Availability to participate in an on-call rotation
• Experience with Azure data services—such as Data Factory, Synapse Analytics, Event Hubs, Delta Lake, Cosmos DB, and Azure DevOps
• Exposure to Big Data technologies, NoSQL databases, Git, Jenkins, CI/CD practices, and Agile delivery methodologies
• Claude Certified Developer or Architect highly preferred; possible opportunity to obtain as a Sparq colleague