Job description

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. 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 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. Preferred Qualifications Strong plus with domain knowledge of SAP, Manufacturing, and/or Quality data and processes. Experience delivering in GxP / 21 CFR Part 11 or comparable regulated environments (life sciences, pharma, medical devices). Experience with Unity Catalog and lakehouse governance at scale. Snowflake-to-Databricks migration experience. Exposure to SAP data (ECC / S/4HANA, CDS views) and SAP data integration patterns (e.g., SAP Business Data Cloud). Bonus if candidate have additional domain knowledge such as Commercial and Finance. Databricks and/or dbt certifications. Familiarity with Power BI / Tableau and enabling BI and conversational-analytics. Competencies We Value Ownership: End-to-end accountability for data products, from design through production support. Engineering Craft: Clean, reusable, well-designed code and pride in auditable, reliable data. System Thinking: Sound design judgment across scale, performance, and cost. Technical Leadership: Raising the bar through standards, reviews, and mentorship. Learning Velocity: Quick to adopt new tools , including AI and applying them pragmatically. Cross-Functional Communication: Partnering effectively with business, AI, and platform teams and explaining trade-offs clearly. The estimated base salary range for the Staff Data Engineer role based in the United States of America is: $141,600 - $212,400. Should the level or location of the role change during the hiring process, the applicable base pay range may be updated accordingly. The range reflects long‑term growth in the role; therefore, most candidates are hired between the minimum and middle of the range. Placement depends on experience, skills, location, and internal equity. Additionally, all employees are eligible for one of our variable cash programs (bonus or commission) and eligible roles may receive equity as part of the compensation package. We offer a wide range of benefits as innovative as our work, including access to genomics sequencing, family planning, health/dental/vision, retirement benefits, and paid time off. We are a company deeply rooted in belonging, promoting an inclusive environment where employees feel valued and empowered to contribute to our mission. Built on a strong foundation, Illumina has always prioritized openness, collaboration, and seeking alternative perspectives to propel innovation in genomics. We are proud to confirm a zero-net gap in pay, regardless of gender, ethnicity, or race. We also have several Employee Resource Groups (ERG) that deliver career development experiences, increase cultural awareness, and offer opportunities to engage in social responsibility. We are proud to be an equal opportunity employer committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, military or veteran status, citizenship status, and genetic information. Illumina conducts background checks on applicants for whom a conditional offer of employment has been made. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable local, state, and federal laws. Background check results may potentially result in the withdrawal of a conditional offer of employment. The background check process and any decisions made as a result shall be made in accordance with all applicable local, state, and federal laws. Illumina prohibits the use of generative artificial intelligence (AI) in the application and interview process. If you require accommodation to complete the application or interview process, please contact accommodations@illumina.com. To learn more, visit: dol.gov. The position will be posted until a final candidate is selected or the requisition has a sufficient number of qualified applicants.

Requirements

Must-haves

What if the work you did every day could impact the lives of people you know? Or all of humanity?
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.
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.
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.
Experience delivering in GxP / 21 CFR Part 11 or comparable regulated environments (life sciences, pharma, medical devices).
Experience with Unity Catalog and lakehouse governance at scale.
Snowflake-to-Databricks migration experience.

Nice-to-haves

Solid software engineering foundation — Git, REST APIs, JSON, CI/CD on at least one cloud environment (AWS preferred).
Preferred Qualifications Strong plus with domain knowledge of SAP, Manufacturing, and/or Quality data and processes.
Exposure to SAP data (ECC / S/4HANA, CDS views) and SAP data integration patterns (e.g., SAP Business Data Cloud). Bonus if candidate have additional domain knowledge such as Commercial and Finance.

Application prep

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Keywords to mirror

aimlpythonsqlrestci/cdaws

Platform: workday
Effort: long

Benefits

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Dental

Vision

Paid Time Off