Manager - Data Engineering

我們做什麼

在 Kenvue，我們意識到日常護理的非凡力量。我們以一個多世紀的傳統為基礎，植根於科學，是標誌性品牌的品牌 - 包括您已經熟悉和喜愛的 NEUTRGENA®、AVEENO、TYLENOL®®、LISTERINE®、JOHNSON'S® 和 BAND-AID®。科學是我們的熱情所在;關心就是我們的才能。

我們是誰

我們的全球團隊由 ~ 22,000 名才華橫溢的員工組成，他們的職場文化中，每個聲音都很重要，每一個貢獻都受到讚賞。 我們熱衷於洞察， 創新並致力於為我們的客戶提供最好的產品。憑藉專業知識和同理心，成為 Kenvuer 意味著每天有能力影響數百萬人。我們以人為本，熱切關懷，以科學贏得信任，以勇氣解決——有絕佳的機會等著您！加入我們，塑造我們和您的未來。有關更多資訊，請按兩下 here.

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你會做什麼

This position is based at Bangalore, Kenvue Global Capability Center, reports to Sr. Manager, Digital Solutions & Business Operations and is based at GCC, Bangalore, India

Who we are

At Kenvue, we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, we’re the house of iconic brands - including Neutrogena, Aveeno, Tylenol, Listerine, Johnson’s and BAND-AID® Brand Adhesive Bandages that you already know and love. Science is our passion; care is our talent. Our global team is made up of ~ 22,000 diverse and brilliant people, passionate about insights, innovation and committed to delivering the best products to our customers. With expertise and empathy, being a Kenvuer means having the power to impact the life of millions of people every day. We put people first, care fiercely, earn trust with science and solve with courage – and have brilliant opportunities waiting for you! Join us in shaping our future–and yours. For more information, click here.

What You Will Do 

The Manager – Data Engineering

Will do End‑to‑end delivery, readiness, and operational stability of enterprise data engineering platforms, with a strong focus on Command Centre / Control Tower enablement.

The role is accountable for backend data preparation, enterprise data models and hierarchies, knowledge graph implementation, data migration, compliance, and 24×5 operations, operating in Azure‑based, GxP and SOX‑regulated environments.

This role partners closely with Data Product teams, Architecture, and Business stakeholders to ensure trusted, consumption‑ready data that powers decision intelligence across Operations and Supply Chain

Core Accountabilities

Command Center Data Enablement

• Own Command Center or equivalent platform data engineering, including backend data preparation, semantic layers, aggregates, and real‑time pipelines.
• Ensure persona‑based, role‑based, and hierarchy‑aware data views for dashboards, workflows, and decisioning.
• Enable data readiness for decision intelligence, alerts, and exception management.

Enterprise Data Models, Hierarchies & Knowledge Graphs

• Validate and re-use enterprise logical, physical, and analytical data models.
• Ensure correct implementation of business hierarchies (product, geography, customer, supply chain, time).
• Lead Graph and Knowledge Graph implementations to model relationships, dependencies, and impact paths across the enterprise.
• Ensure graph models integrate seamlessly with Databricks, lakehouse platforms, and analytical datasets.

Data Readiness & Product Collaboration

• Partner with Data Product teams to define and execute data readiness plans aligned to product roadmaps.
• Ensure data meets quality, completeness, timeliness, and usability standards before consumption.
• Act as the execution bridge between platform engineering and data product ownership.

Data Engineering Delivery & Architecture

• Lead delivery of batch, streaming, IoT, and real‑time data pipelines using Databricks, SQL, and Azure services.
• Ensure alignment with enterprise data architecture and lakehouse standards.
• Own large‑scale data migration and modernization programs.

Compliance, Security & Governance

• Ensure GxP and SOX‑compliant data engineering, including auditability, lineage, traceability, and change controls.
• Partner with Security, Quality, and Compliance teams to maintain regulatory readiness.
• 24×5 Platform Operations
• Own 24×5 data engineering support operations, including L2/L3 support, on‑call models, and escalation paths.
• Ensure SLA adherence, incident management, root‑cause analysis, and platform stability.
• Drive reduction of recurring issues through automation and design improvements.

People & Stakeholder Leadership

• Lead and develop data engineering teams, including delivery and support resources.
• Set clear expectations for delivery quality, data readiness, hierarchy accuracy, and operational stability.
• Act as the primary interface for product, architecture, and business stakeholders.

Must‑Have Experience- 9 to 12 YRS

• Strong expertise in Databricks, SQL, Azure cloud ecosystem, and IoT data ingestion.
• Proven ownership of Command Center / Control Tower data engineering.
• Demonstrated accountability for enterprise data models, hierarchies, and knowledge graphs.
• Experience managing data migration programs and regulated (GxP / SOX) data platforms.
• Ownership of 24×5 data engineering operations and people management.

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