Data Engineer
Location: Primarily remote, with 1- 2 days per week in-office in LondonDuration: 12-month contract (with potential for extension)
ONLY CANDIDATES WITH PREVIOUS FINANCIAL SERVICES EXPERIENCE WILL BE CONSIDERED
Overview:Our client, a respected Financial Services organisation, is embarking on a large-scale data transformation initiative and is seeking an experienced Data Engineer to join their team. This role presents an opportunity to work on a cutting-edge data platform within a financial services environment.
The successful applicant will play a key role in designing, developing, and optimizing data pipelines and architectures using the full Azure stack. They will contribute to the build-out of Data Lakes and data platforms, ensuring high performance, scalability, and robust data governance.Â
Key Responsibilities:-
Design, develop, and optimize scalable data pipelines using Azure Databricks and Spark (Scala, Python, SQL).
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Implement and maintain Delta Lake architectures for structured and unstructured data processing.
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Develop ETL/ELT frameworks for efficient data ingestion into Azure Data Lake.
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Implement robust Data Governance frameworks, focusing on Metadata, Data Quality, Lineage, and Data Access Models.
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Utilize Unity Catalog (or similar Data Governance tools) to manage and control data assets effectively.
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Leverage MS Purview or other metadata/data quality tools such as Collibra, Informatica (MDM, Axon, Data Quality), etc..
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Define and implement Data Modelling best practices to support Data Products and Data Domains.
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Work closely with business stakeholders and data analysts to understand data needs and develop tailored solutions.
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Ensure compliance with regulatory and security standards for handling financial data within a corporate banking environment.
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Support and contribute to the broader data architecture strategy within the organization.
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Expertise in Azure Data Engineering, including:
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Databricks (Workflows, Jobs, Notebooks, and Pipelines)
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Azure Data Lake Storage (ADLS)
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Azure Synapse Analytics (nice to have)
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Azure Functions & Logic Apps for automation
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Azure DevOps (CI/CD for data pipelines)
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Strong Spark programming skills using Scala, Python, and SQL.
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Experience with Delta Lake for ACID-compliant data lake architectures.
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Proficiency in data governance tools, including:
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Unity Catalog (or similar Data Governance/Metadata Management tools)
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MS Purview (or alternatives like Collibra, Informatica, etc.)
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Understanding of financial services data landscapes, particularly within corporate banking.
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Experience designing scalable and efficient ETL/ELT frameworks.
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Solid understanding of Data Modelling principles and how they relate to Data Products and Data Domains.
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Experience in Data Architecture is a strong advantage.
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Extensive experience in Data Engineering within large-scale transformation projects.
- Experience creating Data Governance frameworks / structures alongside a Data Transformation.
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Previous experience working within Financial Services is essential.
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Strong analytical and problem-solving skills with a practical approach to data challenges.
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Excellent communication and stakeholder management skills.
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Self-starter mindset, capable of working independently while collaborating effectively with teams.
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Ability to navigate complex data ecosystems and drive efficiency and innovation.
This is a fantastic opportunity for a Data Engineer with strong Azure expertise and a background in financial services to contribute to a strategic transformation program.