Data Engineer - ML & AI

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\’re 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. 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.

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

Software engineering background
Exposure to building or deploying AI/ML models into a production environment
Previously used AWS data services e.g. Experience using any data streaming technologies/paradigms for real-time or near-real time analytics