Assoc Director- Platform & Data Engineer

IN10 (FCRS = IN010) Novartis Healthcare Private Limited; Hyderabad; On-site; INR 4,000,000 - 7,200,000; Full time

Job summary

IN10 (FCRS = IN010) Novartis Healthcare Private Limited is seeking a senior data engineering leader to design and deliver enterprise data platforms and AI-ready solutions. You will build scalable data pipelines using AWS, Databricks, Snowflake, Spark, and Python, ensuring governance, security, and reliability.

You will lead hands-on development of Databricks, Spark, Delta Lake, and Lakehouse solutions, and drive CI/CD, IaC, and data quality across teams while enabling enterprise GenAI

Qualifications

• Bachelor's or Master's degree in CS, Software/Data Eng, or equivalent practical experience.
• 12+ years in software or data engineering delivering large-scale production data platforms.
• Advanced hands-on Python, SQL, data modeling, ETL/ELT, CDC, batch/streaming/event-driven architectures.
• Strong Spark (PySpark) experience, distributed processing, performance tuning, troubleshooting.
• Hands-on Databricks, Delta Lake, Snowflake in enterprise environments, cloud‑native secure data platforms.
• Knowledge of AWS services, IaC, security, observability, automation, governance, and data quality.

Responsibilities

• Design, build, and optimize scalable data pipelines (batch, streaming, CDC, event-driven).
• Architect secure, resilient data platforms and translate requirements into cloud solutions.
• Lead development of Databricks, Spark, Delta Lake, and Lakehouse initiatives for performance and cost efficiency.
• Implement Snowflake data engineering workflows: ingestion, transformation, governance, and secure access.
• Develop enterprise data foundations with RAG, vector retrieval, and agentic workflows for GenAI use cases.
• Promote CI/CD, IaC, security‑by‑design, observability, governance, and end‑to‑end data product ownership.

Skills

Python

SQL

ETL/ELT

CDC

Batch processing

Streaming

Apache Spark

PySpark

Databricks

Delta Lake

Snowflake

AWS

CI/CD

Infra as Code

Security

Observability

Governance

Data quality

RAG

LLM integration

APIs

SaaS integrations

Context engineering

Agentic workflows

Data modeling

Communication

Mentoring

Education

Bachelor's degree in Computer Science

Master's degree in Computer Science

Data Engineering

Tools

Databricks

Delta Lake

Snowflake

Apache Spark

PySpark

AWS

Job description

Job Description Summary

This role leads the design and delivery of enterprise data platforms and AI‑ready solutions using AWS, Databricks, Snowflake, Spark, and Python. It is a highly hands‑on technical position focused on building scalable data pipelines, integrations, data products, RAG and agentic AI capabilities, while ensuring strong governance, security, reliability, automation, and performance.

Major Accountabilities

• Design, build, and optimize scalable batch, streaming, CDC, and event‑driven data pipelines using modern data engineering best practices and production‑grade Python and SQL.
• Architect secure, resilient, high‑performance data platforms and translate business and technical requirements into scalable cloud‑based solutions.
• Lead hands‑on development and optimization of Databricks, Apache Spark, Delta Lake, and Lakehouse solutions, ensuring reliability, performance, and cost efficiency.
• Design and implement Snowflake data engineering solutions, including ingestion, transformation, governance, orchestration, and secure data consumption patterns.
• Engineer enterprise data platforms on AWS, leveraging cloud‑native services to deliver secure, automated, observable, and highly available data solutions.
• Develop reusable integration frameworks, APIs, CDC processes, and connectivity patterns across enterprise applications, SaaS platforms, governance tools, ERP, and CRM systems.
• Build AI‑ready data foundations, including RAG pipelines, vector retrieval, context engineering, and agentic workflows, enabling enterprise AI and GenAI use cases.
• Drive engineering excellence through CI/CD, Infrastructure as Code, security‑by‑design, observability, governance, mentoring, and end‑to‑end ownership of data products and platform capabilities.

Minimum Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Information Technology, or a related discipline, or equivalent practical experience.
• 12+ years of experience in software engineering and/or data engineering with proven delivery of large‑scale production data platforms.
• Advanced hands‑on expertise in Python, SQL, data modeling, ETL/ELT, CDC, batch, streaming, and event‑driven architectures.
• Strong experience with Apache Spark (PySpark), distributed data processing, performance tuning, and troubleshooting.
• Proven hands‑on experience with Databricks, Delta Lake, and Snowflake in enterprise‑scale environments.
• Deep knowledge of AWS cloud services, cloud‑native data architectures, security, observability, Infrastructure as Code, and automation.
• Experience implementing CI/CD pipelines, automated testing, monitoring, governance, data quality, security controls, and operational support practices.
• Practical exposure to Generative AI technologies, including RAG architectures, embeddings, vector search, LLM integration, context engineering, and agentic workflows.
• Strong understanding of enterprise integration patterns, APIs, SaaS integrations, metadata management, lineage, data governance, and access control frameworks.
• Excellent stakeholder management, communication, mentoring, problem‑solving, and delivery leadership skills with a highly hands‑on engineering mindset.

Why Novartis?

Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world.

Commitment to Diversity and Inclusion: Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.