Data Engineer - Snowflake

BJSS
London, England
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Relation Therapeutics London, United Kingdom
Permanent

Data Engineer, Strategic Account Services

Amazon London, United Kingdom
Permanent

Data Engineer - Security Products, Monitored Access

Amazon London, United Kingdom
£40,000 – £60,000 pa On-site

Senior Data Engineer

Synthesia London, United Kingdom
Hybrid

Senior Research Engineer - Data

Synthesia London, United Kingdom
Remote

Senior Simulation Data Engineer

PhysicsX London, United Kingdom
Posted
27 May 2025 (11 months ago)

About Us We’re an award-winning innovative tech consultancy - a team of creative problem solvers. Since 1993 we’ve been finding better, more sustainable ways to solve complex technology problems for some of the world’s leading organisations and delivered solutions that millions of people use every day. In the last 30 years we won several awards, including a prestigious Queen’s Award for Enterprise in the Innovation category for our Enterprise Agile delivery approach. Operating from 26 locations across the world, we bring together teams of creative experts with diverse backgrounds and experiences, who enjoy working and learning in our collaborative and open culture and are committed to world-class delivery. We want to continue to grow our team with people just like you! About the Role Were building out our Data Engineering practice across multiple levels. Depending on your experience and aspirations, you could be contributing as a key team member, leading a dedicated team, or taking on principal engineer responsibilities across multiple teams and larger strategic projects. The role and responsibilities will be tailored to your experience level and our organisational needs. We are Software Engineers who use SDLC best practices to build scalable, re-usable data solutions to help clients use their data to gain insights, drive decisions, and deliver business value. Clients engage BJSS to take on their complex challenges, looking to us to help deliver results against their business-critical needs which means we get to work with a wide range of tools and technologies and there are always new things to learn. BJSS Data Engineers are specialist software engineers that build, optimise, and maintain data applications, systems and services. This role combines the discipline of software engineering with the knowledge and experience of building solutions to deliver business value. You can expect to get involved in a variety of projects in the cloud (AWS, Azure, GCP), while also gaining opportunities to work with Snowflake, Databricks, BigQuery, and Fabric. We work with near real-time/streaming data, geospatial data and using modern AI-tooling to accelerate development. About You You will need: Minimum of two years of recent experience designing and implementing a full-scale data warehouse solution based on Snowflake A minimum of one year of performing architectural assessments, examining architectural alternatives, and choosing the best solution in collaboration with both IT and business stakeholders Fluent in Python, Java, Scala, or similar Object-Oriented Programming Languages Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases Working knowledge of one or more of the cloud platforms (AWS, Azure, GCP) Experience building ETL/ELT pipelines specifically using DBT for structured and semi-structured datasets Any orchestration toolings such as Airflow, Dagster, Azure Data Factory, Fivetran etc It will be nice to have: Software engineering background Exposure to building or deploying AI/ML models into a production environment Previously used AWS data services e.g. S3, Kinesis, Glue, Athena, DynamoDB, SNS/SQS Experience using any data streaming technologies/paradigms for real-time or near-real time analytics

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.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.