Senior data engineer (azure / microsoft fabric) - banking sector
Job Description
We are seeking a highly skilled
Senior Data Engineer
to join a dynamic team within a leading banking environment. This role is ideal for someone passionate about building scalable, high-performance data platforms and delivering robust data solutions that drive business value.
You will play a key role in designing, developing, and optimising modern data architectures, working with cutting-edge technologies such as
Microsoft Fabric, Azure Data Factory, and Databricks.
Key Responsibilities
Translate business, architectural, and data requirements into scalable technical solutions
Design and build
metadata-driven data ingestion pipelines
using Azure Data Factory and Databricks
Develop and maintain enterprise-grade
Data Warehouses (Kimball methodology)
Build and model data products using
Databricks and Microsoft Fabric
Implement end-to-end data engineering solutions using IDX templates into ODP (One Data Platform)
Drive
Dev Ops best practices , including CI/CD and automation
Perform unit testing, integration testing, and debugging to ensure high-quality deployments
Design and manage Azure infrastructure components and templates
Develop and maintain documentation, governance standards, and best practices
Collaborate with business stakeholders to understand and deliver on data requirements
Apply
data governance and engineering standards
to ensure high-quality, secure data products
Participate actively in data engineering and modelling communities of practice
Support operational processes and shared team responsibilities
Requirements Required Skills & Experience
6+ years' experience
as a Data Engineer / Platform Engineer
Strong experience with
Microsoft Fabric
(Lakehouse, Warehouses, Pipelines, Notebooks, Semantic Models)
Hands‑on experience with
Azure Data Factory, Databricks, and Azure Synapse Analytics
Expertise in
Apache Spark
for large-scale data processing
Strong SQL skills (T-SQL) and data analysis capabilities
Experience with
real-time data streaming
(Azure Event Hubs, Stream Analytics)
Solid understanding of
ETL design and optimisation
Experience with
data governance tools
(Unity Catalog, Microsoft Purview)
Knowledge of
Data Warehouse methodologies
(Kimball, Data Vault 2.0)
Proficiency in
Python, C#, and SQL
Experience with
Azure Dev Ops , CI/CD pipelines, and Infrastructure-as-Code (Bicep, ARM, CLI, Power Shell, Bash)
Understanding of
data mesh architectures
Familiarity with
Azure AD security, authentication, and authorization
Agile delivery experience
Qualifications
Bachelor's Degree in Computer Science or related field (or equivalent experience)
Mandatory:
One or more Microsoft Azure certifications (AZ-900, DP-203, DP-600, or DP-700)
Senior Data Engineer
to join a dynamic team within a leading banking environment. This role is ideal for someone passionate about building scalable, high-performance data platforms and delivering robust data solutions that drive business value.
You will play a key role in designing, developing, and optimising modern data architectures, working with cutting-edge technologies such as
Microsoft Fabric, Azure Data Factory, and Databricks.
Key Responsibilities
Translate business, architectural, and data requirements into scalable technical solutions
Design and build
metadata-driven data ingestion pipelines
using Azure Data Factory and Databricks
Develop and maintain enterprise-grade
Data Warehouses (Kimball methodology)
Build and model data products using
Databricks and Microsoft Fabric
Implement end-to-end data engineering solutions using IDX templates into ODP (One Data Platform)
Drive
Dev Ops best practices , including CI/CD and automation
Perform unit testing, integration testing, and debugging to ensure high-quality deployments
Design and manage Azure infrastructure components and templates
Develop and maintain documentation, governance standards, and best practices
Collaborate with business stakeholders to understand and deliver on data requirements
Apply
data governance and engineering standards
to ensure high-quality, secure data products
Participate actively in data engineering and modelling communities of practice
Support operational processes and shared team responsibilities
Requirements Required Skills & Experience
6+ years' experience
as a Data Engineer / Platform Engineer
Strong experience with
Microsoft Fabric
(Lakehouse, Warehouses, Pipelines, Notebooks, Semantic Models)
Hands‑on experience with
Azure Data Factory, Databricks, and Azure Synapse Analytics
Expertise in
Apache Spark
for large-scale data processing
Strong SQL skills (T-SQL) and data analysis capabilities
Experience with
real-time data streaming
(Azure Event Hubs, Stream Analytics)
Solid understanding of
ETL design and optimisation
Experience with
data governance tools
(Unity Catalog, Microsoft Purview)
Knowledge of
Data Warehouse methodologies
(Kimball, Data Vault 2.0)
Proficiency in
Python, C#, and SQL
Experience with
Azure Dev Ops , CI/CD pipelines, and Infrastructure-as-Code (Bicep, ARM, CLI, Power Shell, Bash)
Understanding of
data mesh architectures
Familiarity with
Azure AD security, authentication, and authorization
Agile delivery experience
Qualifications
Bachelor's Degree in Computer Science or related field (or equivalent experience)
Mandatory:
One or more Microsoft Azure certifications (AZ-900, DP-203, DP-600, or DP-700)