Data Engineer 2

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. Illumina — Enterprise Data Engineering Data Engineer 2 Job Description Role Overview We are seeking a seasoned, hands-on, detail-oriented Data Engineer to join our Data Engineering team. In this role, you will contribute to building, enhancing, and maintaining scalable end-to-end data pipelines, data models, and data products that enable analytics, reporting, and drive business insights. You will work closely with senior engineers, architects, data analysts, and business stakeholders while developing your technical expertise in modern data engineering practices. This role is ideal for individuals who are passionate about data, AI, cloud technologies, and continuous learning, and who are eager to grow into a well-rounded data engineering professional.

Responsibilities Design, develop, enhance, and maintain scalable data ingestion, transformation, and ELT/ETL pipelines using SQL, Python, dbt, Snowflake, Databricks , and modern data engineering frameworks. Build and support data ingestion pipelines for structured, semi-structured, and unstructured data from enterprise applications, cloud platforms, APIs, databases, and file-based sources. Develop reusable dbt data models, macros, snapshots, and tests, following established engineering standards and best practices. Monitor and troubleshoot data pipelines, investigate failures, and resolve data-related issues under the guidance of senior engineers. Monitor, troubleshoot, and optimize production data pipelines in Snowflake / Databricks , and cloud environments by identifying root causes and resolving data processing, transformation, and performance issues. Participate in code reviews, unit testing, and deployment activities following established engineering standards. Collaborate closely with data engineers, architects, analysts, product owners, data scientists, and business stakeholders to understand requirements and deliver high-quality, reusable data products. Leverage AI-assisted development tools (e.g., GitHub Copilot, Microsoft Copilot, or similar) and intelligent automation techniques to improve developer productivity, code quality, testing, documentation, SQL optimization, and troubleshooting. Stay current with emerging data engineering technologies, cloud services, and industry best practices through continuous learning. Continuously enhance technical expertise in Snowflake, Databricks, dbt, cloud data platforms, AI-enabled engineering practices , and modern data engineering technologies while contributing to continuous improvement initiatives.

Requirements 2–4 years of professional experience in Data Engineering, developing and supporting data pipelines, data models, and data products on modern cloud data platforms such as Snowflake and/or Databricks . Proficiency in Python and SQL for developing data ingestion, transformation, and automation solutions. Good understanding of data modeling concepts, including relational and dimensional modeling, with exposure to lakehouse architecture. Hands-on experience building and maintaining ETL/ELT pipelines using modern data engineering tools such as dbt , Spark, or equivalent technologies. Experience working with cloud-based data platforms such as Snowflake , Databricks , and at least one cloud environment ( Azure, AWS, or GCP ).