Senior Data Engineer (Databricks Lead)
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Job Description
Structured overview of role & requirementsAbout This Role
Lead architecture, design, and implementation of enterprise-scale data platforms using Databricks, Snowflake, and AWS focusing on scalability, security, and performance.
Design and optimize large-scale batch and real-time data pipelines leveraging Apache Spark and Kafka, including real-time ingestion and processing with Kafka and Spark Streaming.
Provide technical leadership and mentorship, collaborate with Analytics and AI teams to support Machine Learning, Generative AI, and LLM-based data solutions.
Minimum Requirements
12-16 years of experience in Data Engineering and Data Platform Architecture.
Strong expertise with Databricks, Apache Spark, Snowflake, Kafka, Python, advanced SQL, and AWS Cloud services.
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
Experience leading enterprise-scale data modernization and cloud migration initiatives.
Ideal Candidate Profile
Experienced in leading and architecting modern data platforms integrating batch and real-time processing for analytics and AI workloads.
Strong hands-on technical leadership with proven ability to mentor teams and drive engineering best practices in data engineering domains.
Background includes building scalable ETL/ELT pipelines and integrating APIs (REST, GraphQL, Databricks) supporting enterprise governance and data security.