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职位Nike

Senior Manager Data Engineering, Global Converse, ITC

Nike

Senior Manager Data Engineering, Global Converse, ITC

Nike

Karnataka, India

·

On-site

·

Full-time

·

3w ago

必备技能

Machine Learning

WHO YOU’LL WORK WITH

We are looking for a Senior Manager, Data Engineering, this role typically reports to a Director of Data Engineering within Global Converse Technology (ITC). You will partner with teammates across Engineering, Product & Platform Teams to ensure that the ecosystem of data meets the needs of the business.

WHO WE ARE LOOKING FOR:

We are seeking a Senior Manager, Data Engineering, to be part of a mission critical team within Global Converse in the ITC. You will lead a cross-functional data engineering team/squad to deliver the scalable, reliable, and secure data foundations that power analytics, intelligence, machine learning, and operational decision‑making at Converse. The ideal candidate is a technology leader with strong architectural instincts, a passion for data as a product, and a proven ability to translate business strategy into resilient data platforms that deliver value at scale.

Required Skills:

  • Bachelor’s degree in computer science, Engineering, or equivalent experience

  • 12+ years of experience in data engineering, data platform development, or analytics engineering

  • 4+ years of experience leading and scaling high performing technical teams

  • Proven success designing and operating data platforms at enterprise scale

  • Deep knowledge of data architecture patterns, batch and streaming pipelines, and data modelling

  • Strong understanding of data governance, quality, lineage, and operational best practices

  • Experience enabling analytics and machine learning through robust, well‑designed data foundations

  • Hands‑on experience with modern cloud data technologies such as Databricks, Snowflake, etc.

  • Experience working within large organizations or scaled Agile delivery models

  • Exceptional communication and stakeholder engagement skills

  • Ability to translate complex technical concepts into clear, actionable guidance for diverse audiences

WHAT YOU’LL WORK ON:

Responsibilities:

  • Leading, mentoring, and managing a cross‑functional team of data engineers responsible for building and operating scalable data platforms, pipelines, and services aligned to multi‑year roadmaps

  • Defining and executing the Data Engineering strategy in support of analytics, intelligence, machine learning, and operational use cases

  • Owning the design and implementation of modern data architectures

  • Ensuring data pipelines are reliable, performant, secure, and observable through strong engineering standards and operational excellence

  • Championing data quality, lineage, governance, and metadata practices that enable trust and self‑service consumption

  • Collaborating with platform, security, and engineering partners to ensure compliant and scalable solutions

  • Familiar with Databricks, Snowflake and other database foundational tools

  • Curiosity on how to utilize AI/ML to accelerate work

  • Demonstrated ability to set technical direction, drive trade-offs, and deliver outcomes with cross-functional partners

  • Excellent people leadership, communication, and stakeholder management; ability to recruit and develop top talent

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关于Nike

Nike

Nike

Public

Nike, Inc. is an American athletic footwear and apparel corporation headquartered near Beaverton, Oregon. It is the world's largest supplier of athletic shoes and apparel and a major manufacturer of sports equipment, with revenue in excess of US$46 billion in its fiscal year 2022.

10,001+

员工数

Beaverton

总部位置

$200B

企业估值

评价

4.2

10条评价

工作生活平衡

4.3

薪酬

3.8

企业文化

4.1

职业发展

3.2

管理层

4.0

82%

推荐给朋友

优点

Flexible scheduling and work environment

Great learning opportunities

Positive and supportive culture

缺点

Limited career growth opportunities

Office politics

Challenging upward mobility

薪资范围

33个数据点

Mid/L4

Senior/L5

Mid/L4 · Data Analyst

2份报告

$134,195

年薪总额

基本工资

$116,500

股票

-

奖金

-

$131,895

$136,359

面试经验

4次面试

难度

3.3

/ 5

时长

14-28周

录用率

25%

体验

正面 0%

中性 75%

负面 25%

面试流程

1

Application Review

2

Recruiter Screen

3

Hiring Manager Interview

4

Technical Assessment

5

Final Interview

6

Offer

常见问题

Technical Knowledge

Behavioral/STAR

Past Experience

Culture Fit