Senior Analytics Engineer

August 15

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Creating strategic value through advanced analytics.

Data Science • Data Analytics • Product Development • Location Intelligence • Innovation

51 - 200

Description

• Utilise your Data Engineering expertise to design and implement scalable data pipelines, using tools such as Airflow and dbt • Maintain existing solutions by resolving any issues which are detected and perform root cause analysis to continually improve the stability of our data platforms • Gather requirements from stakeholders to design performant, logical data models which serve high-quality data to dashboards and business users • Produce clear documentation for all the work you do, ensuring that all decisions, assumptions, and limitations are logged • Work with product managers to scope out the enhancement of existing features and development of new ones • Maintain and optimise the backend architecture of our existing Flask/Django-based web applications • Work alongside other Analytics Engineers to deliver improvements to our ways of working e.g. adopting new tools, creating reusable packages of code, etc. • Contribute to their team goals through consistently delivering on projects of ambitious scope and high complexity • Onboard and support junior members of the team, support more senior members of the team with internal and client deliverables and support the implementation of best practices and processes

Requirements

• Prior experience in a Data/Analytics Engineering role, ideally working alongside Analytics or Software Engineering teams • Advanced coding skills in Python with experience with Numpy/Pandas • Strong version control skills, with experience collaborating on large codebases and managing code across different environments • Subject matter expertise in one or two parts of the model and data engineering and are confident at starting to lead others in these areas • Strong data modelling experience, with a knowledge of best practice when designing schemas • Experience building ETL/ELT pipelines with tools such as Airflow and dbt • Strong Data warehousing experience (e.g. Redshift, Snowflake) • Cloud experience, ideally within AWS (S3, EC2, Lambda, etc.) • Experience with Docker is highly desirable • Experience working with unstructured and semi-structured data along with DBMSs designed to store this type of data (e.g. MongoDB) • Experience using data downstream for analytical purposes e.g. building dashboards (PowerBI, Tableau), predictive modelling, etc.

Benefits

• £6,000 per annum training & conference budget to help you upskill and develop your career • Top tier Private Healthcare with Vitality on us • Numerous, perks, discounts, and rewards with major retailers, gym memberships, technology, and travel partners • Participate in our Share Options scheme from day one • Ability to work from abroad for up to one month each year • 25 days of annual leave (not inclusive of Bank Holidays) • Pension scheme • Cycle to work scheme • Plenty of socials, dinners, and fun nights out • A fully stocked supply of breakfast, fruit, and refreshments for the days when you are in the office