Senior Data Engineer - Data Platform

New

JobgetherData engineering

IndiaContractSenior

Salary not disclosed

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Job Details

Languages: Fluent German and English communication skills.
Experience: At least 5 years of professional experience in data engineering.
Required Skills: PythonSQLGitMicrosoft AzureSparkCI/CDDatabricksPySpark

Have at least 5 years of professional experience in data engineering.
Bring strong hands-on experience with Databricks, SQL, Python, Apache Spark, and PySpark.
Have experience designing, developing, and operating scalable data pipelines.
Have advanced knowledge of dbt Core, particularly in Databricks environments.
Have experience with data modeling based on Data Vault 2.0.
Have experience with historical data models, dimensional modeling, data quality testing, and data documentation.
Know Git, CI/CD pipelines, and automated testing practices.
Have practical experience operating data solutions in Microsoft Azure.
Have several years of experience working in a corporate environment.
Have experience with agile methodologies; SAFe knowledge is an advantage.
Communicate fluently in German and English.
Bring strong analytical and problem-solving skills and the ability to resolve complex technical issues independently.
Work independently, in a structured and goal-oriented manner, and adapt to a dynamic environment.

Further develop, maintain, and operate a modern data platform built on Databricks.
Design, develop, optimize, and maintain scalable data pipelines and data products.
Implement data models following Data Vault 2.0 principles.
Develop and manage data transformations using dbt Core on Databricks.
Establish and maintain data quality, testing, and validation processes.
Ensure stable, high-performance, and cost-efficient operation of data solutions in Microsoft Azure.
Work with historical data models, dimensional modeling, and data documentation.
Collaborate with agile project and product teams and stakeholders to deliver data engineering solutions.
Support automation of development, testing, and deployment workflows using CI/CD pipelines.
Apply version control, automated testing, and continuous integration practices.

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