Design and evolve the enterprise Azure Lakehouse architecture, ensuring scalability, performance, and long-term sustainability.
Lead the transformation of classic Data Warehouse environments into modern Lakehouse and Delta Lake-based architectures.
Take architectural ownership from concept through implementation, production rollout, and continuous optimization.
Define and implement architecture principles, standards, patterns, and best practices for data engineering and analytics platforms.
Design and oversee data ingestion, processing, and streaming pipelines using Azure Databricks, Azure Data Factory, Event Hub, and Azure Logic Apps.
Build and optimize data processing solutions using Delta Lake, Spark, Spark Structured Streaming, SQL, and Python.
Define data modeling strategies across data lake and warehouse layers, applying Kimball, Inmon, and Data Vault methodologies.
Collaborate with engineering teams to implement reference architectures, prototypes, and proof-of-concepts.
Enable and coach data engineering teams toward autonomous, high-quality solution development.
Ensure platform designs comply with enterprise security, data protection, and regulatory requirements.
Support advanced analytics, self-service BI, and reporting use cases across the organization.
Work closely with product owners, architects, governance, and business stakeholders in agile delivery environments.
Contribute to continuous improvement of platform architecture, development processes, and operating models.

Requirements

have a degree in (Business) Informatics, Business Administration, or equivalent practical experience
have senior-level experience in Data Platform / Lakehouse Architecture – Expert
have 5+ years of hands-on experience in data engineering or data architecture roles
have proven experience transforming traditional Data Warehouse landscapes into Lakehouse / Delta Lake architectures
have strong architectural ownership mindset, covering design, implementation, and production readiness
have deep hands-on experience with Azure Lakehouse technologies – Advanced to Expert
have strong expertise in Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Event Hub, Azure Synapse, and Azure Logic Apps
have advanced skills in Delta Lake, Spark, Spark Structured Streaming, SQL, and Python
have deep understanding of data lake storage architectures and modern data processing paradigms
have solid knowledge of relational and multidimensional databases
have strong experience with data warehouse modeling approaches (Kimball, Inmon, Data Vault)
have experience designing scalable IT platforms, processes, and operating models
have the ability to define architecture principles, standards, and best practices at enterprise level
have experience implementing prototypes, evaluations, and reference solutions
have strong security and compliance awareness, including handling business-critical and personal data in regulated environments
are comfortable working in agile environments using Scrum or Kanban
have an open, communicative working style and enjoy cross-functional collaboration
demonstrate a solution-oriented, analytical, and structured mindset

Benefits

Financial benefits
Benefits with focus on learning and development
Benefits with focus on health and sport
Benefits with focus on family and work – life balance
Other benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringdata architectureAzure Lakehouse architecturedata ingestiondata processingdata modelingDelta LakeSparkSQLPython

Soft Skills

architectural ownershipcross-functional collaborationsolution-oriented mindsetanalytical mindsetstructured mindsetcoachingcommunicationagile deliverycontinuous improvementleadership