Data Engineer

Arrow Global Group

. Build and maintain ingestion and transformation pipelines on Microsoft Fabric across Landing, Curate and Enrich layers of the medallion architecture .

Posted 11/3/2026full-timeManchester • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining data ingestion and transformation pipelines using Microsoft Fabric, PySpark, and SQL. Proficient in data quality practices, data modeling, and collaboration with cross-functional teams to deliver trusted datasets for analytics.

Highest-signal resume keywords

Data Pipeline DevelopmentPython/PySpark ProficiencyMicrosoft Fabric ExperienceData Quality PracticesGit and CI/CD Familiarity

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringPySparkT-SQLData ModelingData Quality RulesSQLChange Data CaptureFile LoadsAPI LoadsTerraform

Soft Skills

Analytical SkillsVerbal CommunicationWritten Communication

Tools & Technologies

Microsoft FabricDatabricksAzure SynapseAzure Data FactoryPower BIAzure DevOpsSQL ServerSnowflake

Certifications & Qualifications

Microsoft DP-700 Fabric Data Engineer

Industry Keywords

Financial Data DomainsReal EstateCreditBankingNPL Asset Management

Tech Stack

Tools & technologies

AzurePySparkPythonSnowflakeSQLTerraform

About the role

Key responsibilities & impact

Build and maintain ingestion and transformation pipelines on Microsoft Fabric across Landing, Curate and Enrich layers of the medallion architecture
Onboard source systems using reusable ingestion patterns, including Fabric mirroring, change data capture, file loads and API loads
Write and tune PySpark and T-SQL for Lakehouse and Warehouse workloads, including fact and dimension models
Implement data quality rules and validation pipelines; investigate and resolve data issues
Use Git-based development, pull requests, peer review and CI/CD promotion from Dev to UAT to Production
Contribute to Terraform infrastructure-as-code and SQL projects/DACPAC orchestration configuration
Collaborate with Data Stewards, Data Analysts and the Data Architect to translate mapping specifications and business rules into transformations
Maintain source-to-target mappings, transformation rules, documentation and runbooks
Monitor pipeline runs, triage failures and escalate issues
Prepare trusted datasets and Power BI semantic models for portfolio analytics, asset strategy, finance and risk

Requirements

What you’ll need

Experience building data pipelines as a Data Engineer or in a similar role
Strong Python/PySpark and SQL skills
Hands-on experience with Microsoft Fabric, or with Databricks / Azure Synapse / Azure Data Factory and a willingness to move to Fabric
Comfortable with Git, pull requests and CI/CD
Understanding of data modelling (dimensional / medallion) and data quality practices
Strong analytical, verbal and written communication skills
Degree in Computer Science, Information Systems, Data Science or a related field preferred
Experience in financial data domains or in Real Estate, Credit, Banking or NPL Asset Management is desirable
Microsoft certification (e.g. DP-700 Fabric Data Engineer) a plus
Experience with Snowflake, SQL Server, Microsoft Fabric, Azure services, Power BI, Terraform, Azure DevOps, Git, and SQL Database Projects