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Lead Data Engineer EMEA

Cushman & Wakefield

Lead Data Engineer EMEA

Cushman & Wakefield

CW Site - IND - Kochi - Cushman & Wakefield India Private Limited

·

On-site

·

Full-time

·

1w ago

Benefits & Perks

Flexible Hours

Remote Work

Learning Budget

Career Development

Flexible Hours

Remote Work

Learning

Required Skills

Data Engineering

Databricks

PySpark

SQL

Python

Team Leadership

Root Cause Analysis

Data Modeling

Job Title

Lead Data Engineer EMEA:

Job Description Summary

We're building a new data engineering team and looking for a Lead Data Engineer to be instrumental in establishing our data engineering hub. You'll lead a team of 1-2 senior and 2 junior data engineers, taking ownership of our existing Databricks framework while ensuring operational excellence across ~100 data pipelines (and growing).
This is a hands-on technical leadership role where you'll split your time between mentoring your team, maintaining operational stability, and contributing code to deeply understand our systems. You'll have autonomy in how you execute our roadmap—we care about results, not micromanagement.

Job Description:

About the Role:

  • Operational Excellence: Ensure daily pipeline stability through monitoring, troubleshooting, and rapid incident resolution.

  • Team Leadership: Mentor and guide senior and junior engineers through code reviews, pair programming, and technical coaching

  • Pipeline Development : Create new data pipelines using our existing framework; maintain and improve existing pipelines handling transactional, geospatial, and client data

  • Root Cause Analysis: Systematically debug complex issues by diving deep into code and documentation to identify and resolve problems

  • Data Ingestion: Design and implement stable automated ingestion pipelines from diverse sources

  • Framework Stewardship: Maintain and incrementally improve our Databricks-based framework (declarative pipelines, Py Spark logic, Unity Catalog)

  • Quality Assurance: Report on data quality issues and implement improvements

Critical Technical Skills

  • Production Troubleshooting : Expert ability to diagnose and resolve pipeline failures, performance issues, and data quality problems under pressure

  • Root Cause Analysis: Systematic approach to finding issues by analyzing code, logs, and documentation

  • Data Modeling: Design cross-functional data products, establish data contracts, handle complex business rules

  • SQL: Advanced proficiency including window functions, query optimization, MERGE/UPSERT operations

  • Python/Py Spark: Write reusable, parameterized functions; work with various file formats (JSON, CSV, Parquet)

Platform Knowledge:

  • Deep experience with Databricks (Delta Lake, Spark optimization, job orchestration)

  • Familiarity with Azure Synapse and Azure ecosystem

  • Understanding of Unity Catalog for data governance

Soft Skills

  • Patience and Teaching Ability: Capable of mentoring junior engineers through complex technical challenges

  • Independence: Comfortable making technical decisions and driving execution without constant oversight

  • Strong written communication for async updates and documentation

  • Academic education and professional work level

Nice-to-Have Skills

  • Advanced Spark optimization (broadcast joins, salting, partitioning strategies)

  • Geospatial data processing (H3 indexes, spatial SQL, point-in-polygon at scale)

  • Recursive CTEs and complex SQL patterns

  • Structured Streaming for near-real-time processing

  • Infrastructure knowledge (Azure Portal, resource management, CLI)

  • Git workflows and code review practices

What We Offer

  • Autonomy: Own the execution—we set the high-level roadmap, you determine how to achieve it

  • Growth Path: As the team scales to 8-10+ engineers over 18-24 months, potential progression to Data Engineering Manager with full people management responsibilities

  • Technical Foundation: Established architecture, standards, and best practices already in place

  • Work Style: Weekly or bi-weekly sync meetings with async email updates—no micromanagement

Experience:

  • 6-8 years in data engineering or data analysis

  • 4 years hands-on experience with Databricks and Py Spark at scale

  • 2-3 years in a lead or senior role (formal or informal technical leadership)

  • Proven experience leading, mentoring, or building data engineering teams

Why join Cushman & Wakefield?As one of the leading global real estate services firms transforming the way people work, shop and live working at Cushman & Wakefield means you will benefit from;  Being part of a growing global company;  Career development and a promote from within culture;  An organization committed to Diversity and Inclusion
We're committed to providing work-life balance for our people in an inclusive, rewarding environment. We achieve this by providing a flexible and agile work environment by focusing on technology and autonomy to help our people achieve their career ambitions. We focus on career progression and foster a promotion from within culture, leveraging global opportunities to ensure we retain our top talent. We encourage continuous learning and development opportunities to develop personal, professional and technical capabilities, and we reward with a comprehensive employee benefits program.

We have a vision of the future, where people simply belong.

That's why we support and celebrate inclusive causes, not just on days of recognition throughout the year, but every day. We embrace diversity across race, color, religion, sex, national origin, sexual orientation, gender identity or persons with disabilities or protected veteran status. We ensure DEI is part of our DNA as a global community - it means we go way beyond than just talking about it - we live it. If you want to live it too, join us.

INCO: “Cushman & Wakefield”

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About Cushman & Wakefield

Cushman & Wakefield

Cushman & Wakefield Inc. is an American global commercial real estate and property management services firm. The company's corporate headquarters is located in Chicago, Illinois. It is named after co-founders J. Clydesdale Cushman and Bernard Wakefield.

10,001+

Employees

Chicago

Headquarters

Reviews

3.9

42 reviews

Work Life Balance

3.8

Compensation

4.2

Culture

4.0

Career

3.6

Management

3.4

78%

Recommend to a Friend

Pros

Opportunity for career growth

Interesting projects and challenges

Competitive compensation and benefits

Cons

Internal communication could improve

Career progression could be clearer

Work-life balance varies by team

Salary Ranges

0 data points

Mid/L4

Mid/L4 · Data Analyst

0 reports

$75,222

total / year

Base

-

Stock

-

Bonus

-

$63,939

$86,505

Interview Experience

35 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Offer Rate

42%

Experience

Positive 69%

Neutral 16%

Negative 15%

Interview Process

1

Phone Screen

2

Technical Interview

3

Hiring Manager

4

Team Fit

Common Questions

Technical skills

Past experience

Team collaboration

Problem solving