TJ Morris Ltd
The following content displays a map of the jobs location - Liverpool Upto £50,000 per annum (Depending on Experience) Hybrid working based in the office 2 days per week. 28 days paid holiday per annum, rising to 33 days upon 5 years' service (inclusive of bank holidays) Contributable Company pension scheme Employee benefits: Full-time employees receive 28 days of annual leave (inclusive of bank holidays), increasing to 33 days after 5 years of service. Annual leave is pro-rated for part-time or alternative working arrangements. Contributable company pension scheme 10% store discount at all our retail stores MyHB colleague benefits platform with access to: Discounts UK wide on retail, leisure, hospitality venues Employee Assistance Programme with 24/7 confidential counselling and advice line Low-cost voluntary insured health cash plans and cancer cover Job Introduction As a Data Engineer, you will be a valued member of our Data Insights and Analytics team - which sits within the wider IT Infrastructure and Services department. Our team's mission is to harness the power of data to solve business problems and to enable our colleagues to make more informed decisions. We achieve this by translating data into actionable insights, which lead to a better understanding of our customers, colleagues and events around the business, identifying new opportunities and predicting outcomes. The team strives to promote a mature data culture and - together with the wider IT Infrastructure and Services department - seeks to maximise the benefits of technology by sharing best practises and delivering training. Working alongside our Data Analysts, Data Visualisation Engineers, Business Partners and other Data Engineers, you will be responsible for data model development and operations across our technology stack, ensuring that data flows consistently from our business operations to the teams that need it most. By exploiting your Python and SQL skills, you will work with colleagues to design and implement the infrastructure needed to collect, transform, clean and organise data from across the organisation. You will create the data products that sit at the heart of our data led strategy, delivering insights and underpinning our ML & AI ambition. Please note - We aren't looking for the perfect candidate, if you match some but not all of the above requirements then please still apply Job Overview As a Data Engineer, your primary responsibility is to build and maintain the data feeds that underpin the work of the Data Insights and Analytics team You will be responsible for the entire end-to-end of data provisioning, from identification and scoping through design, implementation, testing and ongoing management You will need to employ engineering best practices to create data feeds that are robust, scalable and efficient The core of our data platform is a modern, scalable cloud data warehouse, from which we develop and deploy data products for use across the business You will play a leading role, alongside your IT colleagues, in the management and further development of this critical infrastructure Ensuring that necessary data is continually fed to deployed data science applications and reports Monitoring data flows, job orchestration and patches/releases as necessary Assisting team members in provisioning data for applications and reports in development Optimising data processing and where appropriate, applying distributed methods The successful candidate must have: Strong knowledge of data warehousing solutions, ETL/ELT processes and data quality issues Proficiency in Python Experience in core software engineering practices, e.g. development lifecycle, Git version control, continuous integration etc. Experience with cloud computing Previous experience working as part of a data team Experience with distributed frameworks and containers And it's a bonus if you have the following, but not essential: A good understanding of retail-oriented business processes and systems Familiarity with Snowflake/AWS/Airflow/DBT Previous experience working with Big data
The following content displays a map of the jobs location - Liverpool Upto £50,000 per annum (Depending on Experience) Hybrid working based in the office 2 days per week. 28 days paid holiday per annum, rising to 33 days upon 5 years' service (inclusive of bank holidays) Contributable Company pension scheme Employee benefits: Full-time employees receive 28 days of annual leave (inclusive of bank holidays), increasing to 33 days after 5 years of service. Annual leave is pro-rated for part-time or alternative working arrangements. Contributable company pension scheme 10% store discount at all our retail stores MyHB colleague benefits platform with access to: Discounts UK wide on retail, leisure, hospitality venues Employee Assistance Programme with 24/7 confidential counselling and advice line Low-cost voluntary insured health cash plans and cancer cover Job Introduction As a Data Engineer, you will be a valued member of our Data Insights and Analytics team - which sits within the wider IT Infrastructure and Services department. Our team's mission is to harness the power of data to solve business problems and to enable our colleagues to make more informed decisions. We achieve this by translating data into actionable insights, which lead to a better understanding of our customers, colleagues and events around the business, identifying new opportunities and predicting outcomes. The team strives to promote a mature data culture and - together with the wider IT Infrastructure and Services department - seeks to maximise the benefits of technology by sharing best practises and delivering training. Working alongside our Data Analysts, Data Visualisation Engineers, Business Partners and other Data Engineers, you will be responsible for data model development and operations across our technology stack, ensuring that data flows consistently from our business operations to the teams that need it most. By exploiting your Python and SQL skills, you will work with colleagues to design and implement the infrastructure needed to collect, transform, clean and organise data from across the organisation. You will create the data products that sit at the heart of our data led strategy, delivering insights and underpinning our ML & AI ambition. Please note - We aren't looking for the perfect candidate, if you match some but not all of the above requirements then please still apply Job Overview As a Data Engineer, your primary responsibility is to build and maintain the data feeds that underpin the work of the Data Insights and Analytics team You will be responsible for the entire end-to-end of data provisioning, from identification and scoping through design, implementation, testing and ongoing management You will need to employ engineering best practices to create data feeds that are robust, scalable and efficient The core of our data platform is a modern, scalable cloud data warehouse, from which we develop and deploy data products for use across the business You will play a leading role, alongside your IT colleagues, in the management and further development of this critical infrastructure Ensuring that necessary data is continually fed to deployed data science applications and reports Monitoring data flows, job orchestration and patches/releases as necessary Assisting team members in provisioning data for applications and reports in development Optimising data processing and where appropriate, applying distributed methods The successful candidate must have: Strong knowledge of data warehousing solutions, ETL/ELT processes and data quality issues Proficiency in Python Experience in core software engineering practices, e.g. development lifecycle, Git version control, continuous integration etc. Experience with cloud computing Previous experience working as part of a data team Experience with distributed frameworks and containers And it's a bonus if you have the following, but not essential: A good understanding of retail-oriented business processes and systems Familiarity with Snowflake/AWS/Airflow/DBT Previous experience working with Big data