75-85K SALARY LEVEL

The Client

A well-established Wealth management firm.

The Role

This a new role for a dynamic Data Engineer who will play a pivotal role in the executional delivery of the business data strategy for the Wealth Management firm. There is real scope to expand this role.

The Data Engineer will be building and adding to Data lake infrastructure to enable efficient data access, retrieval, and analysis, proactively identifying and addressing bottlenecks.

The Data Engineer will be required to establish Data lake and design pipelines into it, and requires a balance between technical data ability and communication skills as the Data Engineer role will be working with various teams and stakeholders across the Wealth Management business.

The Data Engineer will confidentially design, develop and maintain data pipelines to ingest, process, and transform large volumes of structured and unstructured data from internal and external sources. These can be on-prem and cloud based, such as CRM Dynamics 365, Mongo DB, SQL, ESP, IMiX, GA4 and other 3rd party connectors and data repositories.

The Data Engineer is to constantly monitor and optimise the performance and scalability of the data lake and pipelines to ensure optimal load and resource utilisation, as well as meeting evolving business needs and data processing requirements.

The Data Engineer will confidently implement data quality governance processes to ensure data integrity, consistency, and compliance with regulatory requirements and industry standards, such as GDPR.

The Data Engineer will stay up to date with new technologies, best practices, and industry trends in data engineering, cloud computing, and big data analytics, and identify opportunities to enhance the data lake environment and drive continuous improvement initiatives.

The Candidate

Bachelor's Degree in Computer Sciences, Math, Software Engineering, Computer Engineering, or related field

2+ years’ experience in business analytics, data science, software development, data modelling or data engineering work,ideally in Tech or Financial Services/FinTech

1+ years’ experience as a Data Engineer manipulating and transforming data in Spark SQL, PySpark, or Spark Scala

1+ years’ experience manipulating and transforming data in T SQL

1+ years’ experience translating business requirements to technical requirements

Proficiency in programming languages such as Python and SQL for data processing,

Experience with big data technologies and frameworks.

Knowledge of cloud computing platforms, in particular Azure, and experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, and Azure Databricks for data storage, processing, and analytics

Knowledge and experience with Git operations, GitHub copilot and CI/CD flows

Familiarity with data visualisation tools and techniques, especially Power BI, for creating interactive dashboards and reports