Director, Full Stack Software Engineering & AI

You will own the data product strategy, dimensional data architecture, engineering standards, platform design and AI roadmap, ensuring our data products are trusted, performant, discoverable, and monetizable.

About You – Experience, Skills & Accomplishments

• Minimum 15+ years in data engineering, software engineering, analytics, or data product leadership, including 4+ years managing managers and global teams

• Proven success building and scaling enterprise-grade data products using software engineering and data modeling best practices

• Deep experience embedding AI, ML, and GenAI into data-centric and analytics-driven products

• Strong data modeling expertise:

  • Dimensional modeling (facts & dimensions)

  • Star and snowflake schema design

  • Conformed dimensions and analytical data models

  • Modeling for BI, analytics, and AI/ML workloads

• Experience creating domain-oriented data models, semantic layers, and metrics frameworks

• Hands-on or architectural experience with cloud-native development (AWS, Azure, or GCP) and data platform engineering

• Proficiency in Python, Java, SQL, microservices, and data-centric application development

• Good knowledge of AWS services (EC2, Lambda, S3, RDS), Docker, Kubernetes, and CI/CD for data/AI workloads

• Expertise with modern data platforms (Snowflake, Databricks, lakehouse architectures, Spark, and streaming frameworks )

• Background in AI/ML frameworks (TensorFlow, PyTorch), MLOps, feature stores, and model lifecycle management will be a plus

• Experience with Generative AI, LLMs, RAG architectures, agentic systems, and MCP (Model Context Protocol) a strong plus

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field

Bonus Points

• Experience delivering commercial data-as-a-product or analytics offerings

• Familiarity with Life Sciences/Healthcare domains (RWE, clinical, or commercial data models)

• Strong passion for customer outcomes, product thinking, and measurable business impact

What You Will Be Doing

Data Product, Analytics & AI Strategy

• Lead and scale a global organization of 30+ engineers delivering large-scale, mission-critical data products trusted by top 20 global pharmaceutical companies

• Define and drive the data product, analytics, and AI roadmap across the LSH portfolio

• Partner with product and business leaders to design analytics-ready, customer-centric data products

• Establish data product ownership, SLAs, quality KPIs, and lifecycle management

• Ensure governance, privacy, and compliance are embedded by design

Software Engineering & Data Modeling

• Lead the design and delivery of software‑engineered, modular, API-first data products

• Own enterprise analytical data models, including dimensional models, star/snowflake schemas, conformed dimensions, and reusable metrics

• Ensure data models support high‑performance analytics, BI, ML, and GenAI use cases

• Champion engineering excellence: test automation, CI/CD, observability, data quality, performance optimization

Data Platform & Analytics Engineering

• Own cloud data platform architecture—lakehouse, streaming, and real-time analytics capabilities

• Enable semantic modeling, analytics engineering, and self-service BI through trusted dimensional models

• Define standards for data quality, lineage, metadata, discoverability, and metric consistency

• Optimize models for scalability, cost efficiency, and performance

AI, GenAI & Intelligent Data Products

• Lead development of AI-powered data products—predictive analytics, GenAI, and LLM-based experiences

• Drive MLOps and LLMOps to operationalize AI at scale

• Explore advanced capabilities such as metrics-aware LLMs, semantic search over dimensional models, and agentic analytics

Leadership & Team Development

• Build, mentor, and grow a high-impact global team across data modeling, data engineering, ML engineering, and platform engineering

• Foster a data-model-driven, product-centric, engineering-first culture

• Lead hiring, talent development, and performance management

Collaboration & Influence

• Partner with product, data science, BI, and business leaders to align metrics, dimensions, and analytical logic

• Communicate data product strategy, modeling decisions, and AI outcomes to senior executives

About the Team

You will join the Life Sciences & Healthcare Commercial Product Engineering organization, leading a globally distributed team across India and the United States focused on delivering high-quality, AI-powered, well-modeled data products at scale.

Hours of work

• Full-time 

• Hybrid working model