Job Description
This role is responsible for designing and developing cloud-native data pipelines, integrating lending application data flows, and enabling analytics and regulatory reporting through well-structured, governed data products. Support the migration of on-premise SSIS workloads to modern, metadata-driven ADF and Databricks pipelines, ensuring performance and scalability improvements.
The successful candidate will collaborate across business, technology, and analytics teams to ensure that data solutions align with Investec s standards for quality, compliance, and performance. This includes supporting the migration from on-premise SQL solutions to the Azure cloud ecosystem.
The role will work closely with our Architect, Engineering lead, Analytics team, DevOps, DBAs, and upstream Application teams in Private Client Technology.Specifically, the person will:
Work closely with end-users and Data Analysts to understand the business and their data requirements
Carry out ad hoc data analysis and data wrangling using Synapse Analytics and Databricks
Building dynamic meta-data driven data ingestion patterns using Azure Data Factory and Databricks
Build and maintain business focused data products and data marts
Build and maintain Azure Analysis Services databases and cubes
Share support and operational duties within the wider engineering and data teams
Work with Architecture and Engineering teams to deliver on these projects. and ensure that supporting code and infrastructure follows best practices outlined by these teams.
Help define test criteria to establish clear conditions for success and ensure alignment with business objectives.
Manage their user stories and acceptance criteria through to production into day-to-day support
Assist in the testing and validation of new requirements and processes to ensure they meet business needs
Stay up-to-date with industry trends and best practices in data engineering
Develop automated data quality, validation, and lineage checks embedded in pipelines.
Contribute to the development of DataOps standards, including CI/CD automation, version control, and automated deployment of data solutions (Azure DevOps).
Embed observability (e.g., Application Insights, Log Analytics) to monitor pipeline performance, latency, and reliability.
Core skills and knowledge
Excellent data analysis and exploration using T-SQL
Strong SQL programming (stored procedures, functions)
Extensive experience with SQL Server and SSIS
Knowledge and experience of data warehouse modelling methodologies (Kimball, dimensional modelling, Data Vault 2.0)
Experience in Azure one or more of the following: Data Factory, Databricks, Synapse Analytics, ADLS Gen2
Experience in building robust and performant ETL processes
Build and maintain Analysis Services databases and cubes (both multidimensional and tabular)
Experience in using source control & ADO
Understanding and experience of deployment pipelines
Excellent analytical and problem-solving skills, with the ability to think critically and strategically.
Strong communication and interpersonal skills, with the ability to engage and influence stakeholders at all levels.
To always act with integrity and embrace the philosophy of treating our customers fairly
Analytical, ability to arrive at solutions that fit current / future business processes
Effective writing and verbal communication
Organisational skills: Ability to effectively manage and co-ordinate themselves.
Ownership and self-motivation
Delivery focus
Assertive, resilient and persistent
Team oriented
Deal well with pressure and highly effective at multi-tasking and juggling priorities
Experience with event-driven architecture and message-based data integration (Azure Service Bus, Event Hub).
Understanding of real-time vs batch data ingestion trade-offs
Knowledge of data governance frameworks, regulatory compliance (MCOB, GDPR, Consumer Duty), and data lineage tracking.
Understanding of data security principles encryption, role-based access, and data masking in regulated environments.
Any other attributes that would be helpful
Deeper programming ability (C#, .Net Core)
Build infrastructure-as-code deployment pipelines
UK Mortgage Experience
Any financial services and banking experience
Microsoft Certified: Azure Data Engineer Associate (DP-203) preferred.
Microsoft Certified: Azure Fundamentals (AZ-900) desirable.
Continuous learning mindset staying current with emerging Azure and DataOps practices.
This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.