Sr Data Engineer

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible.

Overview The Senior Data Engineer is a seasoned, hands-on engineer who designs, builds, and scales data products on our cloud lakehouse, powering analytics, reporting, and AI/ML across Illumina. We are looking for someone with strong proficiency in Python, SQL, and data modeling, a solid understanding of distributed systems and system design who has built and scaled data products on modern cloud platforms such as Databricks and Snowflake. This is a hands-on, senior individual-contributor role with end-to-end ownership and leadership spanning multiple domains such as Supply Chain, Manufacturing and Quality, including mentoring engineers on our global (India-based) team.

Partner across business, AI, and platform teams translating domain needs (e.g., SAP, Manufacturing, Quality) into well-modeled, governed and scalable data products. Design, build, and scale end-to-end data products on Databricks (and interoperating with Snowflake) — from ingestion through curated, analytics-ready datasets following a medallion (Bronze/Silver/Gold) architecture. Develop reusable frameworks, libraries, and standardized patterns in Python (functional and OOP as appropriate) for ingestion, transformation, validation, and publishing. Design robust data models (relational, dimensional, and lakehouse) and apply strong system-design judgment to build performant, reliable distributed data pipelines using Spark, Delta Lake / open table formats, dbt, and SQL. Embed data quality, reconciliation, validation, and governance into pipelines (Unity Catalog: lineage, RBAC, masking, PII handling. Monitoring, alerting, troubleshooting, root-cause analysis, and SLA adherence for business-critical datasets. Adopt AI in day-to-day data and analytics engineering to accelerate development, testing, and optimization. Act as a technical leader — set standards, lead code reviews, contribute to architecture decisions, mentor engineers, and communicate trade-offs to peers and stakeholders.

8+ years of professional data engineering experience building and scaling data products on cloud platforms such as Databricks and/or Snowflake. Strong proficiency in Python, including reusable framework development using functional and object-oriented programming. Advanced SQL and strong data modeling skills (relational, dimensional, and lakehouse). Solid understanding of distributed systems and system design for large-scale data processing. Hands-on experience with open table formats (Delta Lake, and/or Apache Iceberg ) and big-data file formats (Parquet). Experience with Spark and modern ELT tooling (e.g., dbt). Experience with data observability , governance, security, and compliance practices (RBAC, PII, SOX). Demonstrated adoption of AI in data and analytics engineering workflows. Solid software engineering foundation — Git, REST APIs, JSON, CI/CD on at least one cloud environment (AWS preferred). Strong written and verbal communication skills, with the ability to work effectively across business, AI, and platform teams and lead technical discussion. Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or a related field, or equivalent demonstrable experience.

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