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Lead Data Engineer EMEA
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:
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Operational Excellence: Ensure daily pipeline stability through monitoring, troubleshooting, and rapid incident resolution.
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Team Leadership: Mentor and guide senior and junior engineers through code reviews, pair programming, and technical coaching
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Pipeline Development : Create new data pipelines using our existing framework; maintain and improve existing pipelines handling transactional, geospatial, and client data
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Root Cause Analysis: Systematically debug complex issues by diving deep into code and documentation to identify and resolve problems
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Data Ingestion: Design and implement stable automated ingestion pipelines from diverse sources
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Framework Stewardship: Maintain and incrementally improve our Databricks-based framework (declarative pipelines, Py Spark logic, Unity Catalog)
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Quality Assurance: Report on data quality issues and implement improvements
Critical Technical Skills
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Production Troubleshooting : Expert ability to diagnose and resolve pipeline failures, performance issues, and data quality problems under pressure
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Root Cause Analysis: Systematic approach to finding issues by analyzing code, logs, and documentation
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Data Modeling: Design cross-functional data products, establish data contracts, handle complex business rules
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SQL: Advanced proficiency including window functions, query optimization, MERGE/UPSERT operations
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Python/Py Spark: Write reusable, parameterized functions; work with various file formats (JSON, CSV, Parquet)
Platform Knowledge:
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Deep experience with Databricks (Delta Lake, Spark optimization, job orchestration)
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Familiarity with Azure Synapse and Azure ecosystem
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Understanding of Unity Catalog for data governance
Soft Skills
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Patience and Teaching Ability: Capable of mentoring junior engineers through complex technical challenges
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Independence: Comfortable making technical decisions and driving execution without constant oversight
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Strong written communication for async updates and documentation
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Academic education and professional work level
Nice-to-Have Skills
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Advanced Spark optimization (broadcast joins, salting, partitioning strategies)
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Geospatial data processing (H3 indexes, spatial SQL, point-in-polygon at scale)
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Recursive CTEs and complex SQL patterns
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Structured Streaming for near-real-time processing
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Infrastructure knowledge (Azure Portal, resource management, CLI)
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Git workflows and code review practices
What We Offer
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Autonomy: Own the execution—we set the high-level roadmap, you determine how to achieve it
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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
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Technical Foundation: Established architecture, standards, and best practices already in place
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Work Style: Weekly or bi-weekly sync meetings with async email updates—no micromanagement
Experience:
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6-8 years in data engineering or data analysis
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4 years hands-on experience with Databricks and Py Spark at scale
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2-3 years in a lead or senior role (formal or informal technical leadership)
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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
PublicCushman & 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+
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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%
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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
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Bonus
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$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
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