Sr Data Engineer

Apex Fintech Solutions UK
Belfast
1 day ago
Create job alert
Overview

Who We Are
Apex Fintech Solutions (Apex) powers innovation and the future of digital wealth management by building tech-forward solutions that help simplify, automate, and facilitate access to financial markets for all. Our robust suite of fintech software enables us to support clients such as Stash, Betterment, SoFi, Webull, and eToro, amongst many others; collectively, Apex powers access to the stock market for over 22+ million end customers.


Apex is changing how the securities industry operates by reinventing the status quo, which was manual, slow, and accessible only by the ultra-wealthy. We’re digitizing and democratizing systems so that everyone has an opportunity to invest. When you’re at Apex, you drive this change. You’re part of a global team with a clear vision: to be the trusted technology that powers the digital economy. Our offices in Austin, Dallas, Chicago, New York, Portland, Belfast, and Manila are home to over 1,000 employees. Together, we’re shaping the future of financial innovation. Embrace change. Solve big. Win together. And be G.R.E.A.T. — grit, results, empathy, accountability, and teamwork — with Apex.


We’re proud to be recognized for the innovative work we do, the purpose-driven nature of our work, and the collaborative culture we’ve created. Here are just a few of the many awards we’ve recently received:


Best Places to Work 2026, 2025, 2024, 2023
Presented by BuiltIn


WealthTech of the Year 2025
Presented by US FinTech Awards


The World’s Top 250 Fintech Companies 2024
Presented by CNBC


About This Role

Apex Fintech Solutions is seeking a Senior Data Engineer to play a key role on our Billing engineering team, responsible for designing, developing, and maintaining high-quality software solutions. You will leverage your experience and expertise to contribute to the software development lifecycle, from requirements analysis and implementation to testing and deployment. You will collaborate with team members and cross-functional partners to deliver scalable, reliable, and efficient software products that meet the needs of our users and business objectives.


Duties/Responsibilities

  • Design and maintain data pipelines for the classic billing system using Python and MS SQL Server, including ETL processes, data transformations, stored procedures, and scheduled jobs to support financial reporting and reconciliation workflows
  • Build and optimize SQL queries and database objects in MS SQL Server for the legacy system, writing complex queries, views, indexes, and stored procedures to support billing operations, reporting requirements, and data quality checks
  • Develop Python-based automation and data processing scripts to integrate the classic system with modern platforms, handling data extraction, transformation, validation, and loading between MS SQL Server and cloud-based systems like BigQuery and PostgreSQL
  • Support data migration and modernization efforts from the classic billing system to the new microservices platform, designing data mapping strategies, building migration tools, and ensuring data integrity across systems during the transition
  • Create and maintain data quality monitoring, implementing validation checks, reconciliation processes, and alerting mechanisms to ensure accuracy and consistency of billing data across both classic and modern systems
  • Collaborate with engineering and finance teams to understand data requirements, provide data insights for billing calculations and settlements, and support ad-hoc analysis and reporting needs using SQL, Python, and BI tools
  • Document data schemas, pipelines, and processes for both classic and modern systems, creating technical documentation, data dictionaries, and runbooks to support system knowledge transfer and operational continuity

Education And/or Experience

  • Bachelor's degree in Computer Science, Engineering, or related field (or equivalent work experience) required; advanced degree preferred
  • 5+ years of experience in software development with a strong proficiency in one or more programming languages, including Java, Python
  • Experience with automated testing frameworks and methodologies for backend services
  • Experience contributing to epics and participating in technical direction and implementation strategy for projects
  • Experience with CI/CD (Continuous Integration/Continuous Deployment) pipelines and tools, automating build, test, and deployment processes
  • Experience with cloud platforms (e.g., AWS, Azure, GCP)
  • Experience with SQL including the ability to write complex queries and optimise database performance, e.g. Postgres, MS SQL Server
  • Experience in financial services a plus

Required Skills/Abilities

  • Ability to troubleshoot production systems, diagnose issues, and implement effective solutions to ensure system reliability and availability
  • Strong problem-solving abilities, analytical thinking, and attention to detail
  • Effective communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and contribute to technical discussions
  • Knowledge of Agile software development methodologies and tools (e.g., Scrum, Kanban, Jira)

Work Environment

  • This job operates in a hybrid work environment 2 days per week.

#engineering #full-time #mid-senior #AFSUK


Our Rewards

We offer a robust package of employee perks and benefits, including a market-leading salary with an annual bonus, 28 days of annual leave plus 10 Northern Ireland national holidays, a training and development budget, and a pension matched up to 7%. Our benefits also cover private health insurance for medical, dental, and optical care, and life insurance. We emphasize work-life balance with flexible working hours, parental leave, a modern city center office, and a hybrid work schedule that allows for greater flexibility by partially working from home. Additional perks include monthly catered lunches, unlimited drinks and snacks, hackathon events, poker tournaments, and a charitable matching gift program.


EEO Statement

Apex Fintech Solutions is an equal opportunity employer that does not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, veteran status, marital status, or any other protected characteristic. Our hiring practices ensure that all qualified applicants receive fair consideration without regard to these characteristics.


Disability Statement

Apex Fintech Solutions is committed to creating an inclusive and accessible workplace for all candidates, including those with disabilities. We are dedicated to ensuring equal employment opportunities and providing reasonable accommodations to qualified individuals with disabilities. If you require reasonable accommodations to participate in the application or interview process, please submit your request via the Candidate Accommodation Requests Form. We will work with you to provide the necessary accommodations to ensure your full participation in our hiring process.


#J-18808-Ljbffr

Related Jobs

View all jobs

Sr Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.