ABOUT AIVIQ

Aiviq is a cutting-edge fintech company revolutionising financial services and asset management. We empower the world's leading

asset managers with data-driven insights and innovative technology solutions. Our cloud-based platform transforms complex

financial data into actionable intelligence, addressing critical challenges in client data quality and insights. Serving global

asset managers overseeing trillions in Assets under Management, we're at the forefront of financial technology innovation.

Reporting Structure

Reports to: Data Centre of Excellence Team Lead

Dotted line to: Head of Engineering

Location: UK (Hybrid)

Job Purpose

We're seeking an accomplished Data Engineer to join our Data Centre of Excellence while working closely with our Engineering team

on our sophisticated financial data management platform. This role combines the technical depth of enterprise data engineering

with the fast-paced delivery demands of product development, requiring someone who is adept at translating business logic into

code, can think architecturally while attending to implementation details. You'll be the bridge between our data architecture

standards and practical product delivery, ensuring our financial data pipelines are robust, performant, and built on solid

engineering principles.

Key Responsibilities

Data Engineering & Development

Design, build, and optimize data pipelines across Microsoft SQL Server and Azure Synapse Analytics environments
Develop and maintain Spark SQL notebooks for complex data transformations and analysis
Translate business logic and financial calculation requirements into clear, maintainable code
Create data integrity checking scripts and validation frameworks in collaboration with QA teams
Implement automated data quality checks and reconciliation processes
Assist with the maintenance of a curated, anonymized dataset for system testing that covers all known scenarios and edge cases
Analyse production datasets to identify anomalies, debug stored procedures and notebooks, and resolve data quality issues
Demonstrate tenacity in investigating root causes, diving deep into complex problems until resolution is achieved

Architecture & Performance

Consult on database architecture decisions, balancing performance, scalability, and maintainability
Optimize query performance and data processing workflows for large-scale financial datasets
Design and implement solutions using Azure Data Factory, Delta Lake, and related technologies
Think end-to-end about data flows while ensuring rigorous attention to implementation details

Documentation & Process

Create and maintain comprehensive documentation of database schemas, processes, and data flows
Develop visual process models using tools such as Lucidchart, Visio, dbt, Azure Purview, or similar platforms
Document data transformation logic and calculation methodologies for audit and compliance purposes
Contribute to data governance standards and best practices across the organization

Production Support & Collaboration

Act as first point of escalation for high-priority data issues in production environments
Partner with test automation engineers to develop data-driven testing strategies and create data integrity checking scripts
Collaborate across engineering teams using Azure DevOps for CI/CD pipeline development
Support both Data CoE initiatives and product engineering priorities through effective stakeholder management

Required Skills & Experience

Technical Expertise

Database Technologies: Strong proficiency in MS SQL Server and Azure Synapse Analytics
Big Data Processing: Hands-on experience with PySpark, Spark SQL, and notebook-based development
Cloud Platforms: Demonstrable experience with Azure ecosystem (Synapse, Data Factory, Delta Lake)
Programming: Solid coding skills in SQL, Python, and/or C#
Version Control: Experience with Git and Azure DevOps or similar CI/CD platforms
Testing: Experience building out unit and integration test frameworks and processes to ensure pipelines and notebooks and other

code artefacts are fully automation-tested

Domain Knowledge

Ideally a proven track record working with complex financial data and calculations
Understanding of financial data structures, reconciliation processes, and audit requirements
Experience handling temporal data, slowly changing dimensions, and historical data management
Knowledge of data quality frameworks and validation methodologies

Professional Capabilities

Strong analytical and debugging skills for complex data scenarios across stored procedures and notebooks
Relentless problem-solving approach - comfortable digging deep into technical issues and pursuing answers until problems are

fully understood and resolved

Experience with testing principles and data integrity validation
Ability to consult on technical architecture while maintaining pragmatic focus
Excellent documentation and process modelling capabilities

Experience Level

5+ years in data engineering roles with increasing responsibility
Track record of delivering production data systems at scale
Experience working in matrix or cross-functional team structures

Desirable Skills

Knowledge of Azure Purview or data cataloguing solutions
Familiarity with Great Expectations or similar data quality frameworks
Understanding of behaviour-driven development for data testing
Familiarity with data anonymization, masking, and synthetic data generation techniques
Experience with GraphQL APIs and modern application data layers
Exposure to modern data visualization tools (Power BI, Tableau)
Experience with data build tool (dbt) or similar transformation frameworks

Personal Attributes

Essential

Collaborative mindset: Comfortable working across teams with different priorities and technical backgrounds
Detail-oriented: Meticulous about data accuracy while maintaining delivery momentum
Investigative nature: Thrives on troubleshooting complex issues and pursuing problems through multiple layers until fully

resolved

Intensely curious: Demonstrates deep curiosity about existing processes and systems, with a natural drive to investigate how

things work and independently acquire new knowledge

Pragmatic problem-solver: Balances architectural thinking with practical implementation
Clear communicator: Articulates technical concepts to both specialist and generalist audiences
Ownership mentality: Takes responsibility for production systems and follows through on commitments

Cultural Fit

Thrives in a matrix organization with multiple stakeholders
Comfortable with ambiguity and competing priorities
Passionate about engineering excellence and continuous improvement
Values documentation and knowledge sharing
Responds well under pressure during production incidents

What We Offer

Professional Development

Exposure to enterprise-scale financial data systems handling complex calculations
Opportunity to shape data engineering standards across the organization
Work with modern Azure cloud infrastructure and emerging technologies
Collaborate with skilled engineers across test automation, software development, and data teams
Matrix structure providing diverse learning opportunities from both CoE and product perspectives

Work Environment

Hybrid working arrangement with flexibility
Collaborative engineering culture valuing quality and craftsmanship
Investment in tools, training, and professional growth
Meaningful work on systems that impact financial data integrity and business decisions

Role

Senior Data Engineer

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