data engineer in accounting

data engineer in accounting

Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
Enfint

At a Glance

  • Tasks: Design and deliver scalable data pipelines using cutting-edge cloud technologies.
  • Company: Join Menzies, a leading accounting firm with a focus on innovation.
  • Benefits: Enjoy private medical cover, pension matching, and career development opportunities.
  • Other info: Collaborative environment with a focus on coaching and professional growth.
  • Why this job: Make an impact by shaping data solutions that drive smarter decision-making.
  • Qualifications: 5+ years in data engineering with strong SQL and Python skills.

The predicted salary is between 63000 - 77000 £ per year.

Menzies is an accounting firm with over 1,100 colleagues in the UK. Its data and innovation team builds secure data foundations that support reporting, automation, AI and smarter decision‑making across the firm.

Responsibilities:

  • Lead the design and delivery of scalable, resilient data pipelines into BigQuery from internal systems, APIs, databases, files, webhooks and event streams.
  • Shape the engineering approach across Google Cloud Platform, including BigQuery, Cloud Storage, Pub/Sub, Datastream, Cloud Composer/Airflow, Terraform and infrastructure‑as‑code.
  • Set and champion engineering standards for data modelling, dbt transformations, testing, monitoring, documentation, deployment, version control and cost optimisation.
  • Partner with teams across the firm to turn business needs into scalable, reusable data products using internal and external data sources.
  • Embed security, governance and data quality by design, including data lineage, access controls, GDPR compliance, least‑privilege security and handling of sensitive information.
  • Provide technical leadership by reviewing designs and code, mentoring data engineers and analysts, and strengthening engineering capability across the Innovation Team.
  • Enable data delivery through Power BI, automation workflows, AI agents and internal applications.
  • Evaluate technology and integration options and make build-versus‑buy recommendations balancing business value, security, scalability, supportability and cost.
  • Champion data enablement across Menzies and support colleagues in accessing, understanding and using data safely and effectively.
  • Help shape the Innovation Team roadmap by prioritising strategic, repeatable platforms and solutions.

Requirements:

  • 5+ years of hands‑on experience in data engineering, analytics engineering or data platform roles, including senior or leadership‑level work.
  • Advanced SQL and Python skills for building reliable, production‑ready data solutions.
  • Strong experience with cloud data warehouses, ideally BigQuery, and working knowledge of the wider Google Cloud Platform ecosystem.
  • Experience with Airflow/Cloud Composer, dbt, Git/GitHub, CI/CD and Terraform or other infrastructure‑as‑code tooling.
  • Understanding of data modelling, dimensional modelling, orchestration, testing, data quality and operational monitoring.
  • Experience designing and operating production‑grade data pipelines using APIs, databases, flat files, webhooks and message queues.
  • Understanding of data security and governance, including GDPR, role‑based access, secrets management and responsible handling of sensitive information.
  • Ability to turn ambiguous business challenges into clear, pragmatic technical solutions.
  • Strong communication and stakeholder management skills, including explaining complex technical concepts to non‑technical audiences and influencing decisions.
  • Collaborative leadership style with an interest in coaching others, sharing knowledge and raising engineering standards.
  • Ownership, sound judgement and a delivery mindset with a focus on quality, security and risk.

Nice to have:

  • A degree or equivalent experience in computer science, data engineering, software engineering, mathematics, statistics or a related technical discipline.
  • Google Cloud or dbt certifications.
  • Experience in professional services, finance, accounting, legal, tax, audit or another regulated environment.

Conditions:

  • Private medical cover, pension matching and enhanced parental leave.
  • Career development, learning opportunities and career coaching.
  • Agile working.
  • Volunteering days and wellbeing initiatives.
  • Occasional travel to other Menzies offices for workshops, discovery sessions, implementation support and team meetings.

data engineer in accounting employer: Enfint

AJ Bell is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong emphasis on employee growth, you will have the opportunity to mentor junior designers while working on impactful design systems that prioritise accessibility and usability. Enjoy a supportive environment that values proactive communication and offers unique benefits tailored to enhance your professional journey.

Enfint

Contact Details:

Enfint Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land data engineer in accounting

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Enfint!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like data engineer in accounting at Enfint.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Enfint.

Apply Directly through Our Website

When you find a suitable opening like data engineer in accounting at Enfint, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace data engineer in accounting

Data Engineering
Advanced SQL
Python
BigQuery
Google Cloud Platform
Airflow
dbt

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Enfint, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Enfint. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Enfint

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Enfint!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.