Senior Data Engineer (Databricks Lead)

We are seeking a Senior Data Engineer (Databricks Lead) with 12‑16 years of experience to architect, build and optimize large‑scale data platforms using Databricks, Snowflake, Kafka, Spark, Python, SQL and AWS. The role focuses on designing batch and real‑time pipelines, developing ETL/ELT frameworks, integrating APIs, and leading cross‑functional teams to support analytics, AI/ML and Generative AI initiatives.

• Lead the architecture, design and implementation of scalable, secure and high‑performance data platforms using Databricks, Snowflake and AWS
• Design and optimize large‑scale batch and real‑time data pipelines using Spark and Kafka
• Develop and maintain robust ETL/ELT frameworks to ensure data reliability, scalability and performance
• Implement real‑time data ingestion and processing solutions using Kafka and Spark Streaming
• Build automated data integration frameworks leveraging REST APIs, GraphQL APIs and Databricks APIs
• Design cloud‑native data solutions aligned with enterprise governance, security and compliance standards
• Develop data models using Star Schema, Snowflake Schema, Kimball and Inmon methodologies
• Provide technical leadership, architecture guidance and mentorship to engineering teams
• Collaborate with Analytics, Data Science and AI teams to enable Machine Learning, Generative AI and LLM‑based solutions
• Troubleshoot and resolve platform performance bottlenecks and scalability challenges
• Drive engineering best practices, code quality standards and data governance initiatives

• Strong expertise in Databricks and Apache Spark
• Hands‑on experience with Snowflake and modern data warehouse architectures
• Proficiency in Kafka and real‑time stream processing
• Strong programming skills in Python and advanced SQL
• Experience with AWS Cloud Services
• Expertise in designing and implementing ETL/ELT architectures
• Strong understanding of data modeling concepts and methodologies
• Experience integrating systems using REST and GraphQL APIs
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering or related field
• 12‑16 years of experience in Data Engineering and Data Platform Architecture
• Proven experience leading enterprise‑scale data modernization and cloud migration initiatives