Minimum 6 years of experience as a data engineer., Expertise in Apache Spark, Delta Lake, and Azure Databricks., Proficiency in Python programming and complex SQL queries., Strong knowledge of Azure Data Services like ADLS Gen2, Synapse, and Data Factory..
Key responsibilities:
Design and implement cloud-based data architectures and solutions.
Perform requirements analysis and translate them into technical designs.
Develop prototypes, PoCs, and MVPs for innovative data solutions.
Participate in technical project work and provide production support.
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this job:
• Advice on architectural discussions and workshops with customers, understand their business and technical requirements to create the desired technical architectures and solutions on Cloud around data engineering, data lakes, data lakehouses, BI and MLAI.
• Perform requirements scoping exercises with project and use case stakeholders.
• Translate requirements into desired technical solution design.
• Carry out PoCs, prototypes and build MVPs for new innovative solutions and technology scouting on cloud (Azure) and Big Data Technologies.
• Participate in handson technical project work including actual project implementation tasks and some production support tasks (e.g. monitoring) as required.
• Evaluate and implement platform cost optimizations
• Create and maintain technical documentation for the use cases, solutions and data platform.
• Perform analysis of best practices and emerging concepts in Cloud based technologies with special focus on Data and Analytics cloud Ecosystem.
Absolute Musts:
• Indepth knowledge of Apache Spark and experience in optimizing and performance
tuning of Apache Spark data processing jobs
• Indepth knowledge of Delta Lake
• Indepth knowledge of Data Engineering on (Azure) Databricks
• Strong handson experience in Python programming and in writing complex SQL
queries
• Strong handson experience in building complex data pipelines in Azure Data Factory
• Strong handson experience in the following Azure Data Services: ADLS Gen2, Synapse
Serverless
• Experience in architecting and building enterprise grade data platforms on Cloud and
developing Big Data solution architectures preferably on Azure, incl.:
o Gathering requirements and mapping those to technical architectures
o Awareness of best practices for selecting a component mix of Cloud services (e.
g. ADF, Databricks, Synapse, etc.)
o Ability to assess pros and cons of architecture variations (e. g. Databricks vs
Snowflake vs. MS Fabric, Synapse vs MS Fabric Lakehouse, Databricks vs. open
source Spark, …).
Additionally required:
• Multiyear experience working (>6 years) in a data engineer role, incl.:
• Expertise in designing, building and maintaining large scale data pipelines as well as