Data Engineer

Position: Staff Data Engineer
## Staff Data Engineer Apply locations:
US
- California
- San Diegotime type:
Full time posted on:
Posted Yesterday job requisition :
43169-JOBWhat 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.## ## Summary The Staff 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.## ##
** Responsibilities
* ** 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.##
** Required Qualifications
*** 10+ 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…