Data Engineer

SF Recruitment
London
2 weeks ago
Applications closed

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Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

We're supporting a large-scale data programme that requires an experienced Data Engineer to help transform complex, unstructured information into clean, reliable datasets suitable for analysis and reporting. The project involves working with sizeable JSON files and other mixed-format sources, standardising them, and preparing them for downstream use across several internal systems. You'll be responsible for shaping the structure, improving data quality, and ensuring outputs can be easily consumed by non-technical teams. What You'll Work OnConverting varied and unstructured data (including JSON) into well-defined relational formats. Designing data models that ensure consistency and interoperability across tools. Preparing datasets for use in spreadsheets, reporting environments, and CRM systems. Resolving data quality issues: type mismatches, missing values, integrity checks, and formatting problems. Building repeatable processes and validation steps to support accurate, sustainable reporting. Partnering with operational and business teams to understand requirements and ensure outputs are fit for purpose. Skills & Experience NeededStrong SQL abilities and experience designing relational schemas. Hands-on Python skills (preferably pandas) for data wrangling and transformation. Solid understanding of data modelling principles and best practices. Good working knowledge of Excel and awareness of CRM/enterprise da...

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Data Engineering Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

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How to Write a Data Engineering Job Ad That Attracts the Right People

Data engineering is the backbone of modern data-driven organisations. From analytics and machine learning to business intelligence and real-time platforms, data engineers build the pipelines, platforms and infrastructure that make data usable at scale. Yet many employers struggle to attract the right data engineering candidates. Job adverts often generate high application volumes, but few applicants have the practical skills needed to build and maintain production-grade data systems. At the same time, experienced data engineers skip over adverts that feel vague, unrealistic or misaligned with real-world data engineering work. In most cases, the issue is not a shortage of talent — it is the quality and clarity of the job advert. Data engineers are pragmatic, technically rigorous and highly selective. A poorly written job ad signals immature data practices and unclear expectations. A well-written one signals strong engineering culture and serious intent. This guide explains how to write a data engineering job ad that attracts the right people, improves applicant quality and positions your organisation as a credible data employer.

Maths for Data Engineering Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data engineering jobs in the UK, maths can feel like a vague requirement hiding behind phrases like “strong analytical skills”, “performance mindset” or “ability to reason about systems”. Most of the time, hiring managers are not looking for advanced theory. They want confidence with the handful of maths topics that show up in real pipelines: Rates, units & estimation (throughput, cost, latency, storage growth) Statistics for data quality & observability (distributions, percentiles, outliers, variance) Probability for streaming, sampling & approximate results (sketches like HyperLogLog++ & the logic behind false positives) Discrete maths for DAGs, partitioning & systems thinking (graphs, complexity, hashing) Optimisation intuition for SQL plans & Spark performance (joins, shuffles, partition strategy, “what is the bottleneck”) This article is written for UK job seekers targeting roles like Data Engineer, Analytics Engineer, Platform Data Engineer, Data Warehouse Engineer, Streaming Data Engineer or DataOps Engineer.