Lead Data and Analytics Engineer

What you'll do

• Translate business requirements from HR and Corporate Services into technical solution designs.
• Engineer and implement scalable, production-ready data engineering solutions and pipelines.
• Build working prototypes and MVPs quickly to validate solutions with stakeholders.
• Develop batch and real-time data pipelines using Spark, Kafka, or Databricks.
• Prepare enterprise data for AI use cases, including vectorization and RAG architectures.
• Implement data quality, observability, lineage, and governance standards.
• Mentor technical staff in design thinking and agentic development.
• Maintain production-grade software through ongoing monitoring and iterative improvements.

What we're looking for

• Bachelor's Degree with 7 years of experience, Master's with 6 years, or PhD with 2 years of relevant experience.
• Expert-level proficiency in Python and SQL for production-quality code, pipeline automation, and LLM enrichment.
• Experience developing batch and real-time data pipelines using Apache Spark, Kafka, Flink, Databricks, or equivalent.
• Experience with modern cloud data platforms such as Azure, AWS, or Google Cloud.
• Strong knowledge of data modeling, warehousing, data lakes, and data lakehouse architectures.
• Experience implementing data quality, observability, lineage, metadata management, governance, and security.
• Experience preparing enterprise data for AI engineering, including RAG, vector databases, and generative AI applications.
• Experience in pharmaceutical or highly regulated environments, SDLC methodologies, and GxP compliance (preferred).