Data Engineer - HYBRID WORKING

Data Engineer - HYBRID WORKING

We are working exclusively with one of our Financial Serivces clients who are based in the Bristol area.  We are looking for an experienced Data Engineer to join the team on a hybrid working model basis.

The Data Engineer is responsible for

Supporting the Data Engineering Manager with the design and implementation of ELT/ ETL, data movement and data model design and implementation to support the needs of the business, ensuring it:

• Is trusted and fit for purpose
• Is secure, scalable, and performant
• Leverages contemporary technologies and data paradigms as appropriate
• Supports a single analytical view of our data and information
• Implements agreed and defined metrics
• Delivers business value by supporting action-oriented insights

Responsibilities

• Delivery of ETL/ELT processes, data models and data marts from design to implementation
• Documentation of solutions implemented
• Documentation of data lineage
• Responsible for performance, stability, and active monitoring of systems to support ETL/ELT
• Identifying bottlenecks in performance and working with technical teams to overcome any issues
• Supporting the test, support, and release management processes
• Drive best practice through initiative and peer review
• Contribute to the team risk and issues register
• Accountable for maintaining technical standards and governance for delivery in line with the information management data management framework
• Supporting CAB (Change Advisory Board) process to ensure appropriate governance is followed

Essential Skills

• Ability and desire to pick up new technology, tools, paradigms and run with them 
• Experience of implementing cloud centric data solutions using platforms such as Azure 
• Knowledge of automating deployments using a combination of tools such as PowerShell and Azure DevOps 
• Ability to use Python both to manipulate data and building additional process to support data processing activities 
• Experience manipulating, processing and storing data using tools such as SQL, dbt, pyspark and SSIS 
• Comfortable building out and administrating data models, ensuring that they are accessible and used appropriately, leveraging platforms such as Databricks and Power BI, and Microsoft Fabric
• Familiarity with data processing paradigms such as ETL/ ELT, Kimball, Medallion Data Lakehouse
• Passionate about data and information with a strong understanding of data architecture principles and information “story telling” to maximise the value of our raw data
• Strong problem solving and planning skills with a “can do” attitude to manage and mitigate risks to maintain delivery commitments

Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted. 

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