About Illumina:

Illumina is a leading developer, manufacturer, and marketer of life science tools and integrated systems dedicated to making genomics useful for all. Illumina’s integrated Indian global hub in Bengaluru, Illumina India Biotechnology Private Limited, is focused on technology activities that will help usher in the next wave of innovation in healthcare and medical research. If you’re eager to work on challenging projects that uses cutting-edge technology to transform the future of healthcare, this is your chance to join a truly remarkable team.

JOB SUMMARY:

The position is an exciting opportunity to be a member of the Data Integration & Analytics team within GIS Application & Platform Services Dept. The team’s scope includes data services on enterprise data platforms like Snowflake cloud data platform, SAP HANA analytics and Denodo data virtualization. The team is responsible for managing the full software development lifecycle of data, its data quality, and operations. This role will support strategic solutions like the enterprise data lake on AWS/ Snowflake and the enterprise data warehouse on Snowflake. The role is responsible for collaborating with cross functional teams, planning, and coordinating requirements, providing data engineering services and helping build trust in the data being managed.

JOB DUTIES:

• Translate business requirements into data requirements, data warehouse design and sustaining data management strategies on enterprise data platforms like Snowflake.
• Work with project leads, stakeholders, and business SMEs to define technical specifications to develop data modeling requirements and maintain data infrastructure to provide business users with the tools and data needed.
• Solution architect, design and develop large scale and optimized analytics solutions.
• Requirements gathering and analysis, development planning and co-ordination in collaboration with stakeholder teams.
• Understand data requirements & data latency to design & develop data ingestion pipelines
• Design and architect data lake solutions on AWS S3 and Snowflake, considering scalability, automation, security, and performance requirements
• Responsible for architecting, building, and optimizing data lake to store, process and analyze large volumes of structure and unstructured data.
• Understand data architecture & solution design, design & develop dimensional/ semantic data models in an enterprise data warehouse environment.
• Development and automation of enterprise data transformation pipelines
• Work with cross functional teams and process owners on the development of test cases and scripts, test models and solutions to verify that requirements are met and ensuring high levels of data quality.
• Develop and apply quality assurance best practices.
• Design and apply data engineering best practices for data lakes and data warehouses.
• Analyze data and data behaviors to support business user queries.
• Excellent understanding of impact due to changes in data platforms, data models and data behaviors.
• Excellent problem-solving skills and ability to troubleshoot complex data engineering issues.
• Benchmark application operational performance periodically, track (metrics) and fix issues.
• Understand and comply with data governance and compliance practices as defined for risk management. This includes data encryption practices, RBAC and security policies.
• Promote and apply metadata management best practices supporting enterprise data catalogs.
• Support change and release management processes.
• Support incident and response management including problem solving and root cause analysis, documentation.
• Support automation and on-call processes (Tier 1 / Tier 2).

SPECIFIC SKILLS OR OTHER REQUIREMENTS:

• Requires 9 years of experience with:
• Primary Experience: Data Integration and Data Warehousing

Data Platforms:

• Required: Snowflake Cloud Data Platform
• Preferred: SAP HANA analytics

Data Engineering:

• Data Integration: 8+ years of experience working and technologies and ETL/ ELT patterns of data delivery. Strong understanding and experience in implementation of SDLC practices.
• Snowflake: 3+ years of required expertise with Snowflake SnowSQL, Snowpipe (integrated with AWS S3), Streams and Tasks, Stored Procedures, Merge statements, Functions, RBAC, Security Policies, Compute and Storage usage optimization techniques, Performance optimization techniques.
• Dbt Cloud: 2+ years of expertise with dbt cloud platform, very good understanding of data models (views, data materializations, incremental data loads, snapshots), cross functional references, DAGs and its impact, job scheduling, audit and monitoring, working with code repositories, deployments.
• AWS: 2+ years of required expertise with AWS services like S3, Glue, Lambda, Athena.
• Apache Software: Preferred expertise in data processing with Spark & Flink, message broking using Kafka, orchestration using Airflow, processing high data volumes in open table formats like Iceberg.
• HVR (Fivetran): Experience or knowledge on data replication with HVR is a plus.
• SnapLogic: Experience or knowledge on data integrations with SnapLogic is a plus.
• Certifications: Snowflake and dbt Cloud data engineering certifications is a plus.

Source Systems:

• Required: Knowledge and experience integrating data from SAP ERP (On premises, Cloud), Salesforce CRM, Workday, ServiceNow, Relational databases, REST APIs, Flat Files, Cloud Storage

Data Orchestration:

• Required: Control-M, Apache Airflow

Cloud Storage Platforms:

• Required: Amazon Web Services
• Preferred: Microsoft Azure

Programming / Scripting:

• Snowflake: Scripting (Snowpipes, Tasks, Streams, Merge Statements, Stored Procedures, Functions, Security Policies), SQL, Python, PySpark

Code Management:

• Required: Excellent understanding of working with code repositories like GitHub, GitLab ,code version management, branching and merging patterns in a central repository managing cross functional code, deployments.

Data Operations:

• Excellent understanding of Data Ops practices for data management.

Solution Design:

• Good understanding of end-to-end solution architecture and design practices, ability to document solutions (maintain diagrams)

Stakeholder Engagement:

• Ability to take the lead and drive project activities collaborating with Analytics stakeholders and ensure the requirement is completed.

Data Warehousing:

• Excellent on fundamental concepts of dimensional modeling, experience working on data warehouse solutions, requirement gathering, design & build, data analysis, data quality. data validations, developing data transformations using ELT/ ETL patterns.

Data As-A-Product:

• Preferred knowledge and experience working with data treated as data products. Illumina is following a hybrid data mesh architecture which promotes data as a product for data lifecycle management.

Operating Systems:

• Windows, Linux

Experience / Education:

• Typically requires a minimum of 8 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years of experience; or equivalent experience.