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Data Engineer /Databricks
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Data Engineer (Databricks)
Data Engineer (Databricks) is required by a global software company to join its AI and Data team and play a key role in designing, developing, and maintaining data solutions.
Responsibilities:
- Designing, developing, orchestrating, maintaining, and optimizing robust data pipelines and data solutions using Databricks and the Azure ecosystem.
- Building and enhancing structured data models that transform raw data into reliable, business-ready information.
- Implementing data loading, transformation, exploration, and processing solutions.
- Troubleshooting, analyzing, and optimizing ETL processes while performing root cause analysis to improve reliability and performance.
- Supporting CI/CD processes and Agile delivery practices using Azure DevOps, Repos, and pipeline automation.
- Creating and maintaining technical documentation covering workflows, data models, pipelines, and processes.
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Required experience and skills:
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- Extensive experience in a Data Engineering role delivering data pipelines, data warehouses, data lakes, and lakehouse solutions for BI, reporting, and analytics.
- Star Schema, fact and dimension modelling, SCD, and CDC.
- Strong hands-on experience Databricks including Workflows, Delta Live Tables, Delta Sharing, and Unity Catalog.
- Medallion Architecture.
- Apache Spark with DataFrames.
- Experience integrating Databricks with Azure data services, including Azure Data Factory (ADF) and Azure Data Lake Storage Gen2 (ADLS Gen2).
- Advanced SQL and Python.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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