Staff - Master Data Management (MDM) at Illumina

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Biotechnology, Genomics, HealthcareIndustries

Requirements

Bachelor’s degree in information systems, Engineering, Business, or related field (Master’s preferred)
7+ years of experience in Master Data Management, with at least 2-3 years in a leadership or managerial role
Experience working with SAP, Teamcenter, or other PLM/ERP systems is required
Experience in life sciences, manufacturing, or high-regulation industries preferred
Strong understanding of master data domains (material, BOM, customer, vendor, etc.)
Proficient in data governance frameworks and data quality management
Excellent problem-solving, communication, and interpersonal skills
Demonstrated ability to lead cross-functional initiatives and manage competing priorities
Experience with MDM tools (e.g., SAP Master Data Governance, SAP S/4 HANA) is a plus

Responsibilities

Develop and own the enterprise-wide Master Data Management strategy and roadmap
Lead and mentor a team of MDM analysts and specialists
Partner with stakeholders across departments (Operations, Engineering, Supply Chain, IT, Compliance) to define data governance policies and business rules
Oversee end-to-end master data processes, including material master, BOMs, customers, vendors, and other key data domains
Ensure the timely creation, maintenance, and retirement (End of Life) of master data records in systems such as SAP, Teamcenter, and ERP platforms
Implement data quality controls, audit processes, and exception handling workflows
Resolve data-related issues in a timely and accurate manner
Define and enforce data standards, naming conventions, and metadata structures
Collaborate with compliance and regulatory teams to ensure master data adheres to relevant policies and regulations (e.g., FDA, ISO)
Maintain documentation for standard operating procedures and process flows
Serve as the subject matter expert for data models and integrations between SAP, Teamcenter, and other ERP systems
Work with IT and digital transformation teams on MDM tool implementation and automation opportunities

Skills

MDM

SAP

Teamcenter

Data Governance

BOM

Material Master

PLM

Supply Chain

Illumina

Supports genomics startups through funding and resources

About Illumina

Illumina focuses on fostering innovation in the genomics industry by supporting startups through its Illumina Accelerator program. This program helps entrepreneurs create, launch, and grow genomics-focused companies by providing funding and resources. The accelerator operates in two main locations: the San Francisco Bay Area and Cambridge, UK. Illumina Accelerator has successfully invested in 68 genomics startups, which have collectively raised over $1 billion in venture capital. What sets Illumina apart from its competitors is its strong partnership with leading venture capital investors and its dedicated focus on the genomics sector. The goal of Illumina is to build a thriving ecosystem for genomics innovation, enabling new companies to emerge and advance the field.

San Diego, CaliforniaHeadquarters

1998Year Founded

$27.2MTotal Funding

IPOCompany Stage

Venture Capital, BiotechnologyIndustries

5,001-10,000Employees

Risks

Over-reliance on NVIDIA's AI technology may limit flexibility in AI solution adoption.

Standardizing proteomics data across platforms could challenge Illumina's data reliability.

Single-flow-cell NovaSeq X System might cannibalize sales of higher-end models.

Differentiation

Illumina leads in genomic sequencing with advanced AI integration and multiomic data analysis.

The company offers innovative array-based solutions for DNA, RNA, and protein analysis.

Illumina's global expansion includes a new Global Capability Center in Bengaluru.

Upsides

Collaboration with NVIDIA enhances drug discovery and clinical development through AI integration.

Pilot proteomics program with UK Biobank aims to generate crucial reference datasets.

Single-cell sequencing kits make high-throughput sequencing accessible to smaller labs.

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