IT Global Team lead Data engineering

-Lead and manage the global IT team for data engineering that develops all technical artefacts as code implemented in professional IDEs with full version control and CI/CD automation. This team combines both lakehouse modeling of common and business use ase artefacts & semantics as well as generalist data integration & metadata services.
-Ensure high-quality delivery of data engineering assets that enable business analytics AI/ML integration and data governance at scale.
-Act as the delivery and people manager for the data engineering team co-located in Bengaluru collaborating globally with platform business and other IT stakeholders.
-Drive consistency engineering excellence and cross-domain reuse across the entire data engineering lifecyclefrom data acquisition to semantic layer delivery while applying rigorous software engineering practices in data engineering such as modular design test-driven development and artifact reuse in all implementations

-Direct management of approx. 1015 data engineers (generalists and specialists). Reports to the global head of Data & Analytics within the IT Competence Center.
-Team delivers data engineering & analytics assets via Product Owner for data & analytics to all business domains.
-Collaborates with Product Owners Lead Architects & Lead engineers Data Governance Infrastructure & Cybersecurity and domain-aligned functional IT teams globally.

Main Tasks

- Line management for a high-performing cross-functional data engineering team.
- Drive skill development mentorship and performance management.
- Foster a culture of accountability and trust.

- Own timely delivery of data & analytics assets from data acquisition to semantic layers.
- Align work with business priorities and architectural standards.
- Ensure quality gates and documentation.

- Act as primary escalation and coordination point across business domains.
- Bridge infrastructure functional IT cybersecurity and platform decisions.
- Advocate for team in global forums.

- Guide adoption of engineering best practices (TDD CI/CD IaC) & guide building all technical artefacts as code creating scalable batch and streaming pipelines in Azure Databricks using PySpark and/or Scala
-Leading the design and operation of scalable batch/stream pipelines in Databricks including ingestion from structured/semi-structured sources and implementation of bronze/silver/gold layers under lakehouse governance.
-Overseeing dimensional modeling and curated data marts for analytics use cases while ensuring semantic layer compatibility and collaboration on enterprise 3NF warehouse integration.
-Ensuring high-quality engineering practices across data validation CI/CD-enabled TDD performance tuning metadata governance and stakeholder collaboration via agile methods.

- Build an inclusive high-performance team culture in Bengaluru.
- Champion DevSecOps reuse automation and reliability. Commit all artifacts to version control with peer review and CI/CD integration
- Ensure documentation knowledge sharing and continuous improvement.

-Leading the design and operation of scalable secure ingestion servicesincluding CDC delta full-load and SAP extractions via tools like Theobald Extract Universal.
-Overseeing integration with APIs legacy systems Salesforce and file-based sources while aligning all interfaces with cybersecurity standards and compliance protocols.
-Driving the development of the enterprise data catalog application supporting dataset discoverability metadata quality and Unity Catalogaligned access workflows.

Qualifications :

Degree in Computer Science Data Engineering Information Systems or related discipline.
Certifications in software development and data engineering (e.g. Databricks DE Associate Azure Data Engineer or relevant DevOps certifications).

Minimum 8 years in enterprise data engineering including data ingestion and pipeline design. Experience across structured and semi-structured source systems is required. Demonstrated experience building production-grade codebases in IDEs with test coverage and version control.

Hands-on experience with secure SAP/API ingestion lakehouse development in Databricks and metadata-driven data platforms. Delivered high-impact enterprise data products in cross-functional environments.

At least 3 years of team leadership or technical lead experience including hiring mentoring and representing team interests in enterprise-wide planning forums.

Demonstrated success leading globally distributed teams and collaborating with stakeholders across multiple time zones and cultures.

Additional Information :

The well-being of our employees is important to us. Thats why we offer exciting career prospects and support you in achieving a good work-life balance with additional benefits such as:

• Training opportunities
• Mobile and flexible working models
• Sabbaticals

and much more...

Sounds interesting for you Click here to find out more.

Diversity Inclusion & Belonging are important to us and make our company strong and successful. We offer equal opportunities to everyone - regardless of age gender nationality cultural background disability religion ideology or sexual orientation.

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Remote Work :

No

Employment Type :

Full-time