Senior Data Engineer/Power BI Developer

Initialize IT

London, UK

6 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Compensation

£94,640.0

Working hours

Regular working hours

Job source

www.careerboard.com

Tech stack

Data Analysis Extract Transform Load (ETL) Data Flow Control Python (Programming Language) Performance Tuning Power BI Azure Data Lake SQL Stored Procedures SQL Databases Azure Data Factory Sql Optimization Delivery Pipeline

+9 more

Apache Spark Git Powerquery Microsoft Fabric Data Lakes Pyspark Star Schema Data Pipelines Databricks

Job description

Design, develop and optimise ETL and ELT pipelines using Azure Databricks, PySpark, Python and SQL.

Build curated Delta Lake and Lakehouse data products using medallion architecture principles.

Create Microsoft Fabric Lakehouses, notebooks, Dataflow Gen2 ingestion flows and Direct Lake reporting models.

Develop enterprise Power BI datasets, semantic models and dashboards using advanced DAX, Power Query M and star schema modelling.

Implement row-level security, access controls, validation checks and governance standards for production reporting.

Optimise SQL, Spark, Fabric and Power BI workloads for performance, maintainability and cost efficiency.

Work closely with business users, traders, risk teams and finance stakeholders to clarify requirements and deliver production-ready solutions.

Requirements

Global client are looking for a hands-on Senior Data Engineer/Power BI Developer to design, build and support enterprise analytics solutions across trading, risk, finance and post-trade reporting. The role requires strong engineering discipline across Azure Databricks, Microsoft Fabric and Power BI, with the ability to turn complex business requirements into reliable, scalable and well-governed data products.

Essential skills.

Databricks - Delta Lake, Unity Catalog, notebooks, workflows, cluster tuning and production-grade PySpark development.

Microsoft Fabric - Lakehouse, OneLake, shortcuts, Dataflow Gen2, Fabric notebooks, Direct Lake and SQL Analytics Endpoint.

Power BI - DAX, semantic modelling, Power Query M, RLS, incremental refresh, aggregation strategy and performance tuning.

SQL - Advanced SQL, CTEs, window functions, stored procedures, optimisation and large-volume analytical processing.

Azure Data Platform - ADLS Gen2, Azure Data Factory, Git integration, DevOps pipelines and secure cloud engineering practices.

Delivery Mindset - Strong documentation, stakeholder communication, issue resolution and p[rductiopn support experience.