Analytics Engineer in London - Seven Investment Management

About The Role

Purpose:
Reporting to the Head of Data & Analytics, we are seeking a motivated and detail-oriented Analytics Engineer to support our Analytics Engineering capability. This role is ideal for someone with experience in data engineering who is eager to deepen their skills in modern data platforms, particularly Microsoft Fabric and Azure Databricks. You will play a key role in maintaining and evolving our analytics platform, crafting robust data pipelines, and curating high-quality dimensional models to support business intelligence and advanced analytics. You’ll work closely as an enabler to the Data Analyst team, support wider data engineering teams, and ensure analytics platform data is accurate, well-modeled, and traceable.

Responsibilities:
• Platform Ownership: Own and maintain 7IM’s Fabric analytics platform with responsibility for monitoring platform health and resolving issues that arise through usage by the analytics teams.
• Pipeline Development: Build and maintain scalable data pipelines with Fabric and Azure Data Factory to automate ingestion of raw data from various sources and ensure reliability and performance.
• Medallion Architecture: Support the development and maturity of our medallion architecture, ensuring clean separation of raw, refined, and curated data.
• Semantic Modelling: Apply star schema and other best-practice dimensional modelling techniques to transform data into analytics-ready structures. Coach and oversee the implementation of proper semantic modelling by the analytics team.
• Collaboration: Work closely with analytics, insight, and business teams to understand data requirements and deliver solutions that meet their needs. When required, support 7IM’s Data Platform team on wider engineering solutions.
• Governance & Lineage: Implement and maintain data governance practices, including data lineage, documentation, and metadata management. Own the Git version control setup for the analytics team including management of repos, branches and deployment strategy.
• Quality Assurance: Conduct data validation, testing, and monitoring alongside wider testing teams to ensure pipeline integrity and model accuracy.

While not directly interacting with customers, your actions should align with upholding the FCA's Consumer Duty principles, thereby contributing to fair and beneficial outcomes for our clients.

About You

Knowledge:
• Technical experience building and deploying PySpark notebooks in a data warehousing context.
• Strong applied experience using SQL for data transformation and modelling.
• Strong understanding of relational data modelling and data warehousing techniques, including dimensional modelling (e.g. star schema and slowly changing dimensions), with the ability to coach this within a wider team.
• Experience with either Microsoft Fabric or Azure Databricks platforms.
• Exposure to Delta Lake, lakehouse tables, or similar technologies - familiarity with Azure Databricks or Microsoft Fabric in particular is advantageous.
• Experience working with CI/CD including Git implementation.
Beneficial to this role:
• Experience with DAX and Power BI.
• Experience building data pipelines with Azure Data Factory.
• Experience deploying with Terraform within an Azure or Fabric context.
• Awareness of data governance principles and tools (e.g., Purview, Unity Catalog, Fabric Data Governance).
• An understanding of the structure and purpose of the Financial Advice and Wealth Management markets within the UK Financial Services sector is highly advantageous.
• Knowledge of the Agile methodology.

Qualifications:
• No specific qualifications are required for this role; however, relevant qualifications like Fabric Data Engineer Associate or Databricks Certified Data Engineer Associate would be highly advantageous.

Skills/Other relevant information:
• Excellent numerical skills are essential.
• Strong problem-solving and analytical thinking.
• Willingness to learn and grow in a fast-paced environment.
• Good communication skills and ability to work collaboratively.
• Attention to detail and commitment to data quality.

Not Specified

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Analytics Engineer

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