Associate Director

Axtria - Ingenious Insights; Hyderabad; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Axtria - Ingenious Insights in India is seeking a Senior Data Engineering Leader to drive data strategy, modernize platform development, and deliver scalable data products for pharma R&D, Commercial, and Manufacturing use-cases.

You will guide 20-40 engineers across onsite-offshore teams, define robust data ingestion, governance, and Lakehouse architectures using Databricks, Snowflake, and Dataiku, ensuring high-quality ELT/ETL and MLOps practices.

Qualifications

• 12-15 years in Data Engineering with pharma/biotech exposure.
• 5+ years in a leadership role managing 20-40 engineers.
• Proven track record delivering multi-year programs in global environments.
• Certification or hands-on Snowflake, Azure/AWS, and modern orchestration.

Responsibilities

• Lead Data Engineering roadmap and align with global strategy.
• Manage multi-squad teams: Data Engineering, MLOps, Reporting.
• Establish ingestion, transformation, quality, cataloging and lineage standards.
• Drive governance, analytics, and scalable data products for GCC.

Skills

Data Engineering

MLOps

Leadership

Reporting

Cloud platforms

Power BI

Databricks

Snowflake

Airflow

ADF

Data governance

Education

BE/B.Tech

Master of Computer Application

Tools

Databricks

Snowflake

Azure

AWS

Airflow

ADF

Dataiku

Job description

Job Description

Position Summary

Lead a 20-40 member data engineering team supporting global pharma R&D, Commercial, and Manufacturing use-cases. Own data strategy execution, modernize data platform development, and delivery excellence for a Global Capability Center (GCC). Drive scalable data products, governance, and analytics solutions.

Job Responsibilities

Leadership & Strategy

• Own Data Engineering roadmap for enterprise data transformation; align with global data & digital strategy.
• Lead multi-squad engineering teams (Data Engineering, MLOps, Reporting).
• Establish standards for ingestion, transformation, quality, cataloging and lineage.
• Partner with global product owners, business stakeholders, and platform leads across R&D, HEOR, Commercial, Supply Chain.

Technical Delivery

• Architect and scale cloud-native data platforms
• Oversee ingestion pipelines across structured (clinical, commercial, manufacturing) and unstructured data (medical notes, literature, NLP outputs).
• Ensure high-performance ELT/ETL, orchestration, CI/CD, and MLOps practices.
• Manage Lakehouse / Warehouses (Databricks, Snowflake, Dataiku).
• Implement robust data quality KPIs, reconciliation frameworks

Domain Expectations

• Deep understanding of pharma data:
  • Commercial data (IMS/IQVIA, specialty pharmacy feeds)
  • Clinical trial data (CDISC, SDTM, ADaM)
  • RWE/claims/EHR, patient support program data
  • Manufacturing & QC datasets
• Experience delivering data foundations for regulatory submissions, pharmacovigilance, digital biomarkers, omnichannel analytics.

GCC Focus

• Run onsite-offshore governance, delivery dashboards, and stakeholder reporting.
• Drive talent development, vendor management, and operating-model improvements.
• Set up reusable accelerators, playbooks, and delivery frameworks tailored for GCC scale.
• Engage with GCC stakeholders as well as global stakeholders delivering customer delight

Education

• BE/B.Tech
• Master of Computer Application

Work Experience

• 12-15 years in Data Engineering, with 5+ years in pharma/biotech.
• 3-5 years in a leadership role managing 20-40 engineers.
• Proven track record delivering multi-million-dollar programs in global matrixed environments or GCCs.
• Certification or hands-on experience in Snowflake, Azure/AWS, and modern orchestration (Airflow, ADF).

Behavioural Competencies

• Teamwork & Leadership
• Motivation to Learn and Grow
• Ownership
• Cultural Fit
• Talent Management

Technical Competencies

• Problem Solving
• Lifescience Knowledge
• Communication
• Project Management
• Attention to P&L Impact
• Power BI
• Data Governance
• Databricks
• Snowflake
• AWS Data Pipeline