Lead Data Engineer

Overview

Years of Experience:

• Total Experience Required: 7–10 years in Data Engineering
• Healthcare Domain Experience: Minimum 2 years

Job Description:
Industry: Healthcare / AI / Analytics

As a Lead Data Engineer in the healthcare domain, the candidate will be responsible for leading the design and implementation of robust, scalable data pipelines and infrastructure. This role involves close collaboration with data scientists, analysts, and software engineers to ensure seamless data integration across business intelligence and AI platforms.

Key Responsibilities:

• Design, build, and manage scalable data pipelines and architectures for ML, analytics, and reporting.
• Optimize and maintain ETL/ELT processes for reliability, efficiency, and scalability.
• Collaborate with cross-functional teams for data accessibility and integration.
• Implement data governance, security, and compliance with industry standards.
• Lead and mentor junior engineers, promoting knowledge sharing and technical growth.
• Troubleshoot and resolve data-related issues to maintain system performance and uptime.
• Manage project deliverables, work assignments, and communication with stakeholders.
• Stay updated with emerging tools and suggest enhancements to the data infrastructure.

Additional Candidate Preferences:

• Education: Master’s degree in Computer Science or a related discipline
• Preferred Background:
• Experience in healthcare data such as EHRs, wearable or sensor data
• Familiarity with HIPAA, GDPR and healthcare data standards
• Experience in cross-functional collaboration
• Exposure to CI/CD and DevOps practices for data infrastructure
• Soft Skills:
• Strong problem-solving and analytical thinking
• Excellent communication skills for engaging non-technical stakeholders
• Team-oriented, collaborative mindset

Skills RequiredTechnical Skills:

• Programming & Data Processing:
• Python – 5 years (Beginner)
• SQL – 4 years (Beginner)
• Apache Spark – 4 years (Beginner)
• ETL & Data Integration:
• ETL (Extract, Transform, Load) – 5 years (Beginner)
• Data Warehousing – 5 years (Beginner)
• Cloud Platforms:
• AWS – 3 years (Beginner)
• Azure – 3 years (Beginner)
• GCP – 3 years (Beginner)
• Big Data & Real-Time Streaming:
• Apache Kafka – 3 years (Beginner)
• Snowflake – 3 years (Beginner)
• Hadoop – 3 years (Beginner)

Job Types: Full-time, Permanent

Pay: Up to ₹1,800,000.00 per year

Benefits:

• Cell phone reimbursement
• Food provided
• Health insurance
• Paid sick time
• Provident Fund

Schedule:

• Day shift
• Monday to Friday
• Morning shift
• Night shift
• Rotational shift
• Weekend availability

Supplemental Pay:

• Joining bonus
• Performance bonus

Work Location: In person