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Our client a global Bank company is urgently looking for a Senior Data Engineer to work on leading new cloud-data platform. Will be working on transforming raw data into actionable insights, powering decisions across the organisation and solving complex data. Also, Designing, implementing, and maintaining data pipelines and extract, load, transform (ETL) processes to ensure efficient and accurate data flow. Implementing and optimising ETL processes with dbt. Must have experience in Developing and maintaining data models and data architectures within Azure Synapse to support business needs using Kimball methodology and Slowly Changing Dimensions. Using Visual Studio Code for code development, debugging, and version control, ensuring efficient and effective coding practices in Structured Query Language (SQL) / Python. Integrating and automating workflows with Microsoft tools (Power BI, Azure Data Factory, etc.) for efficient data management and reporting.
Keys Skills:-
- ? Experience in Microsoft Azure Synapse, dbt, and Visual Studio Code.
- Strong skills in SQL and Python
- Experience with data integration tools and techniques for combining data from multiple sources.
- Expertise in designing and implementing (Extract Transform Load) ETL pipelines and workflows in Azure Synapse with orchestration
- Design and maintain complex data models and schemas.
- Familiarity with dev ops, and the umbrella of tools used under dev ops such as Git, integrated with Visual Studio Code and Azure Dev Ops.
- Expert knowledge of Microsoft Azure cloud services, with a focus on Azure Synapse, Data Factory, Power BI Service and other related data services.
- General understanding of data transformation and modelling best practices, particularly with dbt.
- General understanding of data governance principles and practices to ensure data quality, integrity, security, and compliance.
- General Understanding of software development lifecycle, including best practices for code development, deployment and environment management.
- intermediate knowledge of APIs and the integration of API sourced data into analytical models
- General understanding of modern data architectures, such as data lakes, warehouses, and cloud-based solutions.
- General understanding of emerging trends, tools and technologies in the Business Intelligence space.
- Expert understanding of stakeholder management principles in the context of data projects.
- Intermediate knowledge of popular Python libraries such as Pandas, NumPy and Pytest
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