Data Engineer 2

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. 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. **Position 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. **Position 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** ). - Familiarity with **Spark** , Delta Lake, Apache Iceberg, or Parquet file formats is preferred. - Exposure to **AI-assisted development tools** (e.g., GitHub Copilot, Microsoft Copilot, or similar) or intelligent automation techniques to improve development productivity, code quality, testing, or documentation. - Strong analytical, troubleshooting, and problem-solving skills with the ability to investigate and resolve data pipeline and production issues. - Effective verbal and written communication skills with the ability to collaborate with data engineers, analysts, architects, product owners, and business stakeholders in an Agile environment. - Demonstrated passion for learning modern data engineering technologies, cloud platforms, and AI-enabled engineering practices. - Bachelor’s degree in Computer science, Information Technology, Engineering, Data Science, Mathematics, or a related field, or equivalent practical experience. **Competencies We Value** - Analytical Thinking & Problem Solving - Analyzes issues, identifies root causes, and delivers practical solutions. - Learning Agility & Continuous Improvement - Quickly learns new technologies and continuously enhances skills and processes. - Ownership & Accountability - Takes responsibility for deliverables and follows through with high-quality outcomes. - Adaptability & Resilience - Adjusts effectively to changing priorities, technologies and business needs. - Innovation & Automation Mindset - Identifies opportunities to automate tasks and improve engineering efficiency. - Curiosity & Continuous Learning - Demonstrates a passion for learning and staying current with emerging technologies, AI, and best practices **.** 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 fou