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EY - GDS Consulting - AI And DATA - Snowflake plus… at EY · Kolkata
ExperiencedOn-siteKolkata
Skills
Advanced SqlAirflowAutomationCapital MarketsArchitectureAutomated TestingCdiscAi
Job Description
Lead - Data Engineering & AI Enablement (Life Sciences) Position Summary
We are seeking a highly experienced and hands-on Data Engineering Leader with 12+ years of experience designing, building, and modernizing enterprise-scale data platforms. The ideal candidate will possess deep expertise across cloud-native data engineering, AI-enabled data modernization, and large-scale analytics platforms, with a strong preference for Life Sciences and Clinical Research domain experience.
This role requires a blend of technical leadership, architecture design, hands-on development, delivery oversight, and client engagement. The candidate will be responsible for leading global engineering teams while actively contributing to architecture, solution design, implementation, optimization, and AI-driven automation initiatives.
Key Responsibilities - Lead end-to-end design, architecture, and implementation of modern cloud-native data platforms and analytics ecosystems.
- Design and develop scalable data ingestion, transformation, orchestration, and consumption frameworks using AWS, Snowflake, Python, and PySpark.
- Modernize legacy ETL and data warehouse solutions through automation, cloud migration, AI adoption, and platform optimization initiatives.
- Architect enterprise data solutions supporting structured, semi-structured, and unstructured datasets.
- Drive implementation of AI/ML and GenAI-enabled capabilities to improve pipeline efficiency, data quality, observability, and operational effectiveness.
- Partner directly with clients to understand business needs, define solution roadmaps, lead workshops, and provide technical advisory services.
- Lead distributed teams of data engineers, architects, and analysts while remaining actively involved in development and code reviews.
- Establish engineering best practices including DevOps, CI/CD, testing, security, monitoring, and governance standards.
- Collaborate with business and clinical stakeholders to translate requirements into scalable technical solutions.
- Drive solution estimation, planning, risk management, and delivery governance.
- Mentor team members and foster a culture of technical excellence and innovation.
- Python
- PySpark / Apache Spark
- Advanced SQL
- Data Modeling
- ETL / ELT Design Patterns
- Data Quality Frameworks
- Metadata-Driven Architectures
- API based Integration
- AWS
- Snowflake
- Dataiku (nice to have)
- PostgresSQL
- Git
- Jenkins
- CI/CD Pipelines
- Infrastructure as Code
- Automated Testing & Deployment
- Environment Management & Release Governance
- AI-enabled Data Engineering
- Pipeline Automation
- Data Observability
- GenAI Adoption for Data Operations
- Intelligent ETL Optimization
- Automated Data Quality & Monitoring Frameworks
- Candidates with Life Sciences, Clinical Development, Biopharma, or Healthcare experience will be strongly preferred.
- Experience working with one or more of the following domains:
- Clinical Trial Data
- Protocol Data
- Participant/Subject Data
- Study Operations , Case Report Forms
- Central Laboratory Data
- Sample Lifecycle Management
- Biomarker & Assay Data
- Clinical Research Platforms
- CDISC / SDTM Standards
- Proven experience leading teams of 10+ engineers across multiple workstreams.
- Strong stakeholder management and executive communication skills.
- Ability to independently lead client meetings, workshops, solution reviews, and architecture discussions.
- Experience managing onsite/offshore delivery models.
- Demonstrated ability to influence technical and business decision-making at senior leadership levels.
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Data Science, or related discipline.
- 12+ years of progressive experience in Data Engineering, Cloud Data Platforms, and Analytics Solutions.
- Experience leading large-scale transformation and modernization programs.
- Cloud certifications (AWS, Snowflake, AI/ML) are highly desirable.