Lead data Engineer
Content + Source + Freshness • 13 Dec 2025 • 95% confidence
Offer value
Very high value role due to critical data engineering skills, significant project responsibility, and scope for technical advancement.
- Key role with significant impact on data strategy.
- Diverse technologies fostering career advancement.
- High demand for experienced professionals.
Pros
- Strong demand for data engineers in the market ensures job security
- Opportunities for advanced technical skill development in multiple technologies
- Role involves working with cutting-edge data management solutions
Cons
- Requires extensive experience and advanced technical skills
- High pressure environment with tight project deadlines
- Long hours may be expected to meet project goals
Who it's for
Senior • On-site
Good fit
- Senior data engineers with strong technical background.
- Professionals passionate about data solutions and cloud technology.
- Individuals ready to lead and innovate in complex data environments.
Not recommended for
- Entry-level engineers without relevant experience.
- Candidates uneasy in high-pressure situations.
- Those preferring to avoid project management responsibilities.
Motivation fit
Key skills
About the job
Expertise in Data Architecture, Data Strategy and Roadmap for large and complex organization and systems and implemented large scale end-to-end Data Management & Analytics solutions
Experience in transforming traditional Data Warehousing approaches to Big Data based approaches and proven track record of managing risks and data security
Expertise with Dimensional modeling techniques, Star & Snowflake schemas, modeling slowly changing dimensions and role playing dimensions, dimensional hierarchies, and data classification
Experiences in cloud native principals, designs and deployments.
Extensive experience working with and enhancing Continuous Integration (CI) and Continuous Development (CD) environments
Expertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival
Data Migration strategies using appropriate tools
Drive delivery in a matrixed environment working with various internal IT partners
Demonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneously
Must be able to work independently and have skills in planning, strategy, estimation, scheduling,
Strong problem solving, influencing, communication, and presentation skills, self-starter
Strong Hands-on programming skills in PySpark
Experience with data processing frameworks and platforms ( Kafka, Beam, Flink, SAP HANA, Hadoop, Presto, Tez, Hive, Spark etc.)
Hands-on experience with related/complementary open source software platforms and languages (e.g. Java, Linux, Python, GIT, Jenkins, MLOps)
Hands-on experience with BI tools and reporting software (e.g. MS PowerBI and Cognos Reporting)
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