LEAD DATA ENGINEER - DATA

Job Title: Lead Data Engineer

Role Overview:

We are seeking a seasoned Lead Data Engineer to guide and mentor engineering teams while developing and maintaining a cutting-edge streaming data platform for a leading healthcare CRM product. You will lead technical design, implement scalable solutions using Python, SQL, Kafka, and cloud technologies, and ensure high performance and quality across the platform.

Technical Requirements:

• Proven experience (9+ years) writing SQL queries for data analysis and reporting.
• 9+ years hands-on experience developing with native Python; additional scripting languages a plus.
• Strong understanding of software engineering concepts, programming methodologies, and the full SDLC.
• Experience leading teams or managing direct reports, with coaching and mentoring skills.
• Strong experience with CI/CD pipelines (Git, Jenkins).
• Hands-on with Docker, Kubernetes, and AWS (Glue, lamda, redshift, EMR, S3, Kinesis) or equivalent cloud platforms.
• Experience with TDD, automated testing, and ensuring code quality.
• Understanding of large-scale distributed systems and enterprise scalability requirements.
• Excellent time management, prioritization, and agile delivery skills.

Key Skills:

• Python | SQL | NodeJS | Scala
• Kafka | Relational and NoSQL databases
• CI/CD (Git, Jenkins) | Docker | Kubernetes
• AWS (Glue, lamda, redshift, EMR, S3, Kinesis) or other cloud services
• Leadership, mentorship, and technical architecture design
• Agile methodology

Work Mode - 4days from Office & 1 day from home

Location - Bangalore

Key Responsibilities:

• Mentor and guide engineering teams in all aspects of the SDLC.
• Lead technical design sessions and translate ideas into robust technical architecture.
• Develop and maintain scalable, high-performance data pipelines and streaming systems.
• Use Python, SQL, Scala, NodeJS, and work with relational databases, NoSQL stores, and Kafka.
• Refactor and optimize legacy codebases for improved performance and scalability.
• Collaborate with product and engineering teams to deliver innovative solutions in an agile environment.
• Support technical support teams with ad-hoc data queries and operational troubleshooting.
• Ensure data pipelines and APIs meet enterprise-grade performance and usability standards.