Lead Engineer - Data & AI
India - Chennai
AstraZeneca
AstraZeneca is a global, science-led biopharmaceutical business and our innovative medicines are used by millions of patients worldwide.Job Title: Lead Engineer - Data & AI
Career Level: E
Introduction to role:
Are you ready to redefine an industry and change lives? AstraZeneca is seeking a seasoned AI and Data Engineering manager to join our Data Analytics and AI (DA&AI) organization. In this pivotal role, you'll be instrumental in shaping and delivering next-generation data platforms, data mesh, and AI capabilities that drive our digital transformation. Your expertise will be crucial in building data infrastructure that supports enterprise-scale data platforms and AI Analytics deployment, fueling intelligent operations across the business.
Accountabilities:
Technical & AI Leadership
- Lead and mentor a multi-functional team of data and AI engineers to deliver scalable, AI-ready data products and pipelines.
- Define and enforce standard processes for Data engineering, data pipeline orchestration, and ELT/ETL development lifecycle management.
- Guide the development of solutions that integrate data engineering with machine learning, foundational models, and semantic enrichment.
AI-Driven Data Engineering
- Architect and develop data pipelines using tools such as DBT, Apache Airflow, and Snowflake, optimized to support both analytics and AI/ML workloads.
- Design infrastructures that facilitate automated feature engineering, metadata tracking, and real-time model inference.
- Enable large-scale data ingestion, preparation, and transformation to support AI use cases such as forecasting, natural language querying/processing (NLQ/P), and intelligent automation.
Governance and Metadata Management
- Have an approach to adhere to data governance and compliance practices that ensure trust, transparency, and explainability in AI outputs.
- Manage and scale enterprise metadata frameworks using tools like Collibra, aligning with FAIR data principles and AI ethics guidelines.
- Establish traceability across data lineage, model lineage, and business outcomes.
Stakeholder Engagement
- Act as a trusted technical advisor to business leaders across enabling functions (e.g., Finance, M&A, GBS), helping translate strategic goals into AI-driven data solutions.
- Lead delivery across multiple workstreams, ensuring measurable KPIs and adoption of both data and AI capabilities.
Essential Skills/Experience:
- 12+ years of hands-on experience in data engineering and AI-enabling infrastructure, with expertise in: DBT, Apache Airflow, Snowflake, PostgreSQL, Amazon Redshift
- 2+ years working with or supporting AI/ML teams in building production-ready pipelines and infrastructure.
- Strong communication skills with a demonstrated ability to influence both technical and non-technical collaborators.
- Experience in implementing data products by applying data mesh principles.
- Experience working across enabling business units such as Finance, HR, and M&A.
Academic Qualifications:
Bachelor’s or Master’s degree in computer science, Information Technology, or related field with relevant industrial experiences.
Desirable Skills/Experience:
- Proficiency in Python, especially in libraries like Pandas, NumPy, and Scikit-learn for data and ML workflows.
- Exposure to ML lifecycle tools such as SageMaker, MLflow, Azure ML, or Databricks.
- Exposure to foundational AI models (e.g., LLMs), vector databases, and retrieval-augmented generation (RAG) methodologies.
- Knowledge of data cataloguing tools such as Collibra, semantic data models, ontologies, and business glossary tools.
When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
At AstraZeneca, your work has a direct impact on patients by transforming our ability to develop life-changing medicines. We empower the business to perform at its peak by combining innovative science with leading digital technology platforms. With a passion for impacting lives through data, analytics, AI, machine learning, and more, we are at a crucial stage of our journey to become a digital and data-led enterprise. Here you can innovate, take ownership, experiment with groundbreaking technology, and tackle challenges that have never been addressed before. Our dynamic environment offers countless opportunities to learn and grow while contributing to something far bigger.
Ready to make a meaningful impact? Apply now to join our team!
Date Posted
28-May-2025Closing Date
10-Jun-2025AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Azure Computer Science Data Analytics Databricks Data governance Data pipelines dbt ELT Engineering ETL Feature engineering Finance Industrial KPIs LLMs Machine Learning MLFlow Model inference NumPy Pandas Pipelines PostgreSQL Python RAG Redshift SageMaker Scikit-learn Snowflake
Perks/benefits: Career development Flex hours
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