About Medline: Medline has a rich legacy of 100+ years of business in the Healthcare segment. We at Medline India have completed around 12 years of our operations and currently have a 1000+ strong and growing team of technology, finance & and business support professionals who support our businesses worldwide towards a mission to make healthcare run better. We are an organization with a conducive work environment, ample opportunities to learn, contribute and grow and a highly empowered & engaged team.
We encourage our people to share their best ideas and create new opportunities for our customers and ourselves to work together to solve today’s toughest healthcare challenges. These are testimonies to Medline been consistently ranked as Best Employers in multiple categories by Forbes for the last couple of years. We have also been listed at #16 place on Fortune 500 list with $20 Billion sales last year.
At Medline
India # PeopleMatter What do we offer :
An employee-friendly work culture, fair & transparent practices, continuous learning and competitive pay and leading employee benefits.
Encouragement to transition to different streams / roles as everything is ‘in-house’ Prospects to work on latest & greatest technologies, value added analytics High focus on quality and dynamic work environment with abundant career development opportunities Flexible work schedule ensuring a perfect work life balance Ample employee-centric benefits fostering employee health and wellbeing Inspiration to create positive social & workplace change.
Role Overview We are seeking a highly skilled Lead - MDM &
- Analytics to drive end‑to‑end data excellence, process governance, and analytical transformation across business functions. This is a critical role which would necessitate a hands‑on technical leader with strongMDM, JavaScript, SQL, Python, data engineering, and visualization expertise, combined with strong critical thinking and the ability to influence stakeholders; be accountable for solution design, technical oversight and strategic delivery.
Experience in AI/ML and a basic understanding of finance are valuable but not mandatory.
Key Responsibilities 1.
Master Data Management
Leadership Lead MDM strategy, architecture, and implementation across Finance domains.
Define and govern data quality rules, match–merge strategies, hierarchies, and survivorship logic.
Oversee MDM workflows, stewardship, metadata, and lineage documentation.
Collaborate with IT, Data Engineering, and Business teams to ensure a unified source of truth.2.
Business
Support &
- Analytics Leadership Partner with business stakeholders to frame problems, collect requirements, and translate them into analytical solutions.
Drive end‑to‑end design of dashboards, KPIs, and decision systems using Power BI and Tableau.
Deliver actionable insights that directly influence operational, strategic, and executive decision‑making.
Mentor and guide analysts and engineers in analytical best practices.3. Engineering &
- Automation Build and review JavaScript solutions for automation, data validation, integration, and UI extensions.
Own and optimize complex SQL queries, stored procedures, data models, and transformation pipelines.
Use Python for ETL/ELT, data wrangling, ML experiments, and automation tasks.
Partner with data engineering teams to design scalable data pipelines and quality checks.4.
Process
Governance &
- Operational Excellence Establish strong process governance, including RACI, change management, quality controls, and audit readiness.
Define and improve business processes with documentation (BRDs, functional specs, SOPs, runbooks).
Drive root‑cause analysis, prioritization, and continuous improvement cycles.
Ensure compliance with data policies, access controls, and risk frameworks.
- Leadership &
- Stakeholder Management Lead cross‑functional initiatives that require technical depth and business context.
Coach team members on analytics, engineering practices, and problem‑solving.
Build a roadmap for data maturity, automation, and analytical enablement.
Communicate progress, risks, and insights to senior leadership.
Required Qualifications Strong hands‑on expertise in MDM: data modeling, DQ rules, survivorship, match/merge, stewardship workflows.
JavaScript (Must‑Have): deep experience building utilities, validation logic, API integrations, or workflow scripts.
SQL proficiency: advanced SQL, query optimization, joins, window functions, and modeling.
Data Engineering skills: ETL design, data pipeline concepts, structured/unstructured data handling.
Python coding: data processing, automation, API consumption, basic ML exposure.
Visualization tools: strong knowledge of Power BI and/or Tableau (DAX, LODs, parameters, modeling).
BSA Skills: gathering requirements, process mapping, UAT, documentation, stakeholder engagement.
Critical Thinking: ability to structure complex problems, derive insights, and influence decisions.
Track Record of Delivery: must have notable accomplishments and measurable outcomes in prior roles. Preferred / Good‑to‑Have Skills Understanding of AI &
- ML concepts (modeling, feature engineering, deployment basics).
Comfort with financial processes or finance domain concepts (not mandatory).
Exposure to cloud data platforms (Azure, AWS, GCP).
Experience with MDM tools such as Reltio, Informatica, Semarchy, Ataccama, or similar.
Knowledge of data governance frameworks, cataloging, and metadata management.
Experience working in Agile environments.
Education &
Experience Bachelor’s or master’s in engineering, Computer Science, Information Systems, Data Analytics, or related field.
Typically, 7–12 years of experience, including leadership or senior individual contributor roles.
Demonstrated success owning and delivering data, analytics, or MDM projects end‑to‑end.
Success
Metrics (First 12 Months) Significant improvement in data quality, MDM accuracy, and master data completeness.
Delivery of well‑adopted analytics products with clear business impact.
Establishment of process governance frameworks and measurable reduction in defects or rework.
Delivery of automation and engineering initiatives that reduce manual effort.
Strong cross‑functional relationships and trust with business and technology partners.
📌 Lead - Master Database Management & Analytics (Pune)
🏢 Finance
📍 Pune