National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Engineer

Levy Professionals
London
1 week ago
Create job alert

As a Senior Data Engineer, you will be responsible for the development of complex data sources and pipelines into our data platform (i.e. Snowflake) along with other data applications (i.e. Azure, Airflow, etc.) and automation.


The Senior Data Engineer will work closely with the data, Architecture, Business Analyst, Data Stewards to integrate and align requirements, specifications and constraints of each element of the requirement. They will also need to help identify gaps in resources, technology, or capabilities required, and work with the data engineering team to identify and implement solutions where appropriate.


Work type: Contract

Length: initial 6 months

Work structure: hybrid 2 days a week in London.


Primary Responsibilities:

  • Integrate data from multiple on prem and cloud sources and systems. Handle data ingestion, transformation, and consolidation to create a unified and reliable data foundation for analysis and reporting.
  • Develop data transformation routines to clean, normalize, and aggregate data. Apply data processing techniques to handle complex data structures, handle missing or inconsistent data, and prepare the data for analysis, reporting, or machine learning tasks.
  • Implement data de-identification/data masking in line with company standards.
  • Monitor data pipelines and data systems to detect and resolve issues promptly.
  • Develop monitoring tools to automate error handling mechanisms to ensure data integrity and system reliability.
  • Utilize data quality tools like Great Expectations or Soda to ensure the accuracy, reliability, and integrity of data throughout its lifecycle.
  • Create & maintain data pipelines using Airflow & Snowflake as primary tools
  • Create SQL Stored procs to perform complex transformation
  • Understand data requirements and design optimal pipelines to fulfil the use-cases
  • Creating logical & physical data models to ensure data integrity is maintained
  • CI CD pipeline creation & automation using GIT & GIT Actions
  • Tuning and optimizing data processes


Qualifications

Required Qualifications:

· Bachelor's degree in Computer Science or a related field.

· Proven hands-on experience as a Data Engineer.

· Proficiency in SQL (any flavor), with experience using Window functions and advanced features.

· Excellent communication skills.

· Strong knowledge of Python.

· Familiarity with Azure Services such as Blobs, Functions, Azure Data Factory, Service Principal, Containers, Key Vault, etc.

· In-depth knowledge of Snowflake architecture, features, and best practices.

· Experience with CI/CD pipelines using Git and Git Actions.

· Knowledge of various data modeling techniques, including Star Schema, Dimensional models, and Data Vault.

· Hands-on experience with:

· Developing data pipelines (Snowflake), writing complex SQL queries.

· Building ETL/ELT/data pipelines.

· Kubernetes and Linux containers (e.g., Docker).

· Related/complementary open-source software platforms and languages (e.g., Scala, Python, Java, Linux).

· Experience with both relational (RDBMS) and non-relational databases.

· Analytical and problem-solving skills applied to big data datasets.

· Experience working on projects with agile/scrum methodologies and high-performing teams.

· Good understanding of access control, data masking, and row access policies.

· Exposure to DevOps methodology.

· Knowledge of data warehousing principles, architecture, and implementation.

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer (SQL Server / AWS)

Senior Data Engineer - Snowflake - £100,000 - London - Hybrid

Senior Data Engineer

National AI Awards 2025

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.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.