Lead Data Solutions Architect

Sr. Data Engineer (Databricks)

About the Role

We’re looking for a hands-on Data Engineer to build reliable, scalable data pipelines on Databricks. You’ll turn requirements into production-grade ELT / ETL jobs, Delta Lake tables, and reusable components that speed up our teams. In this role, you’ll implement and improve reference patterns, optimize Spark for performance and cost, apply best practices with Unity Catalog and workflow orchestration, and ship high-quality code others can build on. If you love solving data problems at scale and empowering teammates through clean, well-documented solutions, you’ll thrive here.

Core Qualifications :

• Bachelor’s degree in computer science, Engineering, or a related field
• 7+ years of experience in software / data engineering, including at least 2 years working with Databricks and Apache Spark
• Strong proficiency in Python, SQL, and PySpark
• Deep understanding of AWS and Azure Cloud service
• Experience with Databricks Data LakeHouse, Databricks Workflows, and Databricks SQL, dbt
• Solid grasp of data Lakehouse and warehousing architecture
• Prior experience supporting AI / ML workflows, including training data pipelines and model deployment support
• Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
• Strong analytical and troubleshooting skills in a fast-paced, agile environment
• Excellent collaboration skills for interfacing with both technical and non-technical customer stakeholders
• Clear communicator with strong documentation habits
• Comfortable leading discussions, offering strategic input, and mentoring others

Key Responsibilities :