Data Engineering Lead

Job Title: Data Engineering Lead (mAI – Data Foundation Core)

Location Preference

1st: Zurich, Switzerland

2nd: Anywhere in Switzerland

3rd: Anywhere in the European Union

Experience:

12–15+ years in Data Engineering, Cloud Data Platforms, Data Architecture, and Enterprise Data Solutions.

Role Summary:

Lead the Data Foundation for AI platform by designing scalable AWS-based data architecture, building enterprise data pipelines, establishing governance, and enabling reusable data services for Insights Generator, Value Dossier, Pricing, OSS, and mAI Assistant.

Key Responsibilities:

Lead the architecture and implementation of AWS-based structured and unstructured data platforms supporting AI and GenAI solutions.

Design scalable data ingestion pipelines, data models, metadata, lineage, data quality, and governance frameworks.

Establish reusable data contracts, integration patterns, and secure data access across enterprise AI products.

Collaborate with Takeda Enterprise Architecture, Data Engineering, AI, Security, and Product teams to define the Data Foundation roadmap.

Drive engineering standards, technical reviews, backlog prioritization, and mentor distributed engineering teams.

Required Skills:

AWS: S3, Glue, Lambda, Athena, Redshift, EMR, Lake Formation, Step Functions, Event Bridge, API Gateway, IAM

Python, PySpark, SQL

Apache Spark, Kafka (preferred)

Data Lake/Lakehouse architecture

Data Governance, Metadata, Lineage, Data Quality

GenAI, RAG, Vector Databases, Knowledge Graphs

Terraform, GitHub, CI/CD

Excellent stakeholder management and communication