IT Engineer Data Lakehouse – Tech Lead

Job Description

Key targets of the job profile

* Govern the enterprise-wide standards for data & analytics modeling and performance within the Databricks Lakehouse.
* Drive consistency and reuse of core data & analytics artifacts and ensure scalable integration across all business domains.
* Provide expert consulting, quality assurance, and enablement for data engineering and data science teams.
* Act as a design authority for data warehouse, semantic modeling, and advanced analytics integration.

Dimensions/ Organization/Magnitude

* Acts as the senior engineering point of contact for the lakehouse layer across global teams.
* Coordinates with 25+ data engineering and data science professionals across domains and geographies.
* Collaborates closely with platform architects, data scientists, governance teams, and functional IT globally.

Main Tasks:

Data & Analytics Model Governance

• Define enterprise 3NF and warehouse modeling standards.
• Maintain and review enterprise-wide data & analytics models and shared artifacts.
• Align naming conventions and metadata handling with governance standards.

Lakehouse Performance & Semantics

• Guide partitioning, indexing, and performance tuning.
• Enable, steer and optimize semantic integration with Power BI, live tabular exploration and other tools.
• Own common functions, e.g. FX conversion, BOM logic, time-slicing.

Quality Gate & Design Authority

• Review and approve core components for quality and reusability.
• Provide support on high-performance or high-complexity challenges.
• Align lakehouse implementation with architectural decisions.

Advanced Analytics Integration

• Collaborate with data science and AI teams on model deployment.
• Ensure seamless integration of ML/AI pipelines into the lakehouse.
• Support LLM and external API integration patterns.

Developer Enablement & Reusability

• Build and maintain shared libraries and data engineering templates. 
• Coach junior engineers and define TDD and "as-code" standards.
• Drive engineering excellence across the community of practice.

Documentation & Standards

• Maintain architectural blueprints, templates, and best practices.
• Publish design guidelines and coding standards.
• Create re-usable architecture patterns for lakehouse environments.

Performance & Cost Optimization

• Monitor usage and implement auto-scaling policies.
• Analyze and optimize cluster configurations for cost-efficiency.
• Provide cost transparency and usage reporting to stakeholders.

Summary:

This role is pivotal in shaping the semantic and performance foundation of the enterprise-wide data & analytics platform. By driving standardization and governance in core modeling practices, this position ensures that data engineering and data science teams can build scalable, high-performing, and reusable solutions aligned with business and analytics goals.

Qualifications

Education / Certification: Degree in Computer Science or related field; certifications in Databricks or Microsoft preferred.

Professional Experience: 6–10 years in data engineering with focus on enterprise data & analytics warehouse, lakehouse modeling, and ML integration.

Project and/or Process Experience: Hands-on experience designing large-scale semantic, warehouse, and advanced analytics layers.

Leadership Experience: Track record of architectural ownership and peer enablement with diverse teams.

Intercultural / International Experience: Experience working in international teams across multiple time zones and cultures, preferably with teams in India, Germany, and the Philippines.

Required skills: 

• PySpark, Scala, Delta Lake, Unity Catalog, Power BI integration               
• Dimensional and 3NF modeling, semantic layer design                     
• ML model lifecycle integration, MLOps patterns, LLM APIs                        
• Test-driven development, performance profiling                  
• Metadata strategy, lineage tracking, naming standards       
• Cross-domain business logic patterns (e.g., KPIs, hierarchies)           
• Reporting & BI tools (e.g. tabular analysis tools) and dashboarding tools (preferably Power BI) 
• Advanced analytics (Data Mining & other KDD) and machine learning concepts and methodologies   
• AI service (e.g. LLM) & API integration concepts

Additional Information

What we offer:

The 13-th salary – Paid once a year, in December;
Meal tickets - With a value of 40 Ron;
Private Health Insurance – Health is the most important, so we offer you a medical subscription through Signal Iduna;
Referral bonuses - We encourage colleagues to refer new candidates to us and, at the same time, to get the chance to receive a bonus;
Bookster – Feed your body and your mind. You can borrow books and you’ll receive them at the office;
Sports benefits- It’s important to stay active, so we offer you the 7Card;
Discounts at our partners – We collaborate with different vendors, and we receive discounts for various products/ services like rubbers, restaurants, kindergartens, etc;
System for Rewarding Improvement Ideas – We have an internal improvement program (Continental Idea Management) that gives you the opportunity to come up with ideas and to be honored with an attractive bonus (this is established by the CIM team according to your improvement idea);
Happy days – If you or your child is getting married, or you become a parent, you receive some extra free days;
Life events celebration - If your family is growing, we praise your newborn with a bonus;
Unfortunate events - In case of unhappy events in your life, we support you by offering you free days and financial support (handled on a case by-case basis);
Extra vacation days – You begin with 22 vacation days/year, and starting with the 3rd year with us, we offer you 1 more day of vacation and. We reward employees who reach 15 and 20 years within the company with another day of vacation, reaching a maximum of 29 days.
Professional development - Many opportunities to develop yourself within the company;
Diversity and multicultural mindset - We encourage you to join us no matter who, where, or what you are. We have colleagues from different nations and a variety of languages are spoken in our company.

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