Data Engineer

Translucent Ltd; United Kingdom; Remote; GBP 70,000 - 105,000; Full time

Job summary

A leading company in the accounting sector is seeking a product-minded Data Engineer to enhance their data platform. The role involves designing data pipelines, ensuring data quality, and embedding AI features. Ideal candidates have extensive experience with SQL and Python, alongside a product-focused mindset. The position is remote-first, allowing for flexibility within the UK/PT timezone.

Benefits

Equity options

23 days holiday

Top-tier laptop

Qualifications

• 5+ years building and maintaining production data pipelines.
• Deep expertise in SQL & Python, data-warehouse modelling.
• Hands-on with modern BI tools and applied AI workflows.

Responsibilities

• Design & build data pipelines from various platforms.
• Own the modern data stack and set standards for quality.
• Embed AI in products and partner with teams for data-driven features.

Skills

SQL

Python

Data Governance

Data Quality

Tools

dbt

Airflow

Snowflake

BigQuery

Looker

Hex

Mode

Job description

Translucent is revolutionising the accounting landscape by addressing the financial challenges faced by 5-7 % of companies globally. Founded by seasoned entrepreneurs who previously exited a multi-million-dollar business and have led teams at some of the world’s best-known firms, Translucent brings unparalleled expertise. Honoured as Xero App of the Year 2022 & 2023 , we’re headquartered in London but operate fully remotely in the UK/PT timezone (±2 hours). We meet in person twice a year and hold regular off-sites to spark collaboration and innovation.

About the role

We’re looking for a product-minded Data Engineer who loves turning messy, real-world data into clean, reliable fuel for decision-making and AI-powered features. You’ll be the force behind our modern data platform—designing pipelines, championing data quality, and building self-serve tooling so every Translucent team (Product, Sales, Ops, Finance, Customer Success) can dive deep without waiting in a queue.

Our culture is one of relentless curiosity and bias-for-action. You’ll sit in a small, cross-functional squad, shipping end-to-end: from ingest to warehouse to dashboards to user-facing product features that leverage applied AI (think embeddings, vector search, LLM-powered enrichment). If you enjoy both heads-down engineering and white-boarding product ideas with designers or CFOs, you’ll feel right at home.

What you'll do

• Design & build pipelines that ingest data from accounting platforms, CRMs, and internal services into our warehouse and feature stores (batch + streaming).
• Own the modern data stack (dbt, Airflow/Prefect, Snowflake/BigQuery, event streams) and set the standards for testing, observability, and data quality.
• Empower everyone by creating clear, documented marts, metrics layers, and self-serve dashboards; be the go-to mentor for SQL, BI, and experiment design.
• Embed AI in the product —work with ML engineers to productionise models, store embeddings, and expose real-time features to our front-end via APIs.
• Partner with Product & Growth to understand user pain points, prototype data-driven features, and measure impact.
• Set direction for data governance, security, and privacy, balancing speed with regulatory requirements.
• Continuously improve —measure what you ship, iterate, and share learnings across the company.

Requirements

• 5+ years building and maintaining production data pipelines or similar backend systems at scale.
• Deep expertise in SQL & Python , data-warehouse modelling, and orchestration frameworks.
• Hands-on with one or more modern BI tools (e.g. Looker, Hex, Mode) and a track record of enabling self-service analytics.
• Practical knowledge of applied AI / ML workflows—vector databases, feature stores, model monitoring, or LLM integration is a big plus.
• A product mindset —you measure success by the customer and business outcomes your data products unlock, not by rows processed.
• Comfort navigating an early-stage, fast-moving environment: you can unblock yourself, choose scrappy vs. scalable when appropriate, and communicate clearly with technical and non-technical peers.
• Experience with accounting or fintech data sources is nice to have, but curiosity and quick learning trump specific domain knowledge.
• Salary: Up to £105k p.a. + equity options
• Time off: 23 days holiday + the days between Christmas & New Year + local public holidays
• Location: Remote first (UK/PT timezone ±2 hours) with twice-annual team onsites and regular regional meet-ups
• Gear: Top-tier laptop and the tools you need to do your best work