Engineering Manager (Data Platform & Analytics Engineering)

RequirementsPeople-First Leader: You are passionate about developing others and helping people become the best version of themselves, with a strong focus on Diversity, Equity, and InclusionExperienced Manager: You are a dedicated leader who enables collective success and has experience leading data-oriented teams of engineersTechnical Expert: You can draw on significant experience in data and analytics engineering to deliver high-quality, actionable data pipelinesArchitectural Mindset: You have experience designing and building data pipelines, strategic data architectural decisions, and high-quality "data mart" objects across functions like product, finance, or strategyPipeline Specialist: You possess extensive experience in engineering robust ETL/ELT processes and data pipelines, with a focus on curating, transforming, and publishing dataData Governance Focused: You have solid experience in implementing data models, master data management, and data quality rulesStrong Communicator: You have excellent presentation skills and can articulate results clearly to both technical and non-technical senior stakeholdersStack Proficient: You have experience working with a modern analytics stack, including SQL, GitHub, Python, BI tooling (e.g., Tableau), and native cloud services like AWS or GCP(Desirable) Orchestration Mastery: Deep experience with data orchestration tooling such as dbt or dataform(Desirable) Platform Specifics: Hands-on experience with Databricks(Desirable) Modeling Expertise: Practical knowledge of Kimball’s dimensional modelingWhat the job involvesYou will be joining the Kaluza Data community. Data is the foundation of everything we do as an organisation, and to deliver our vision we need curious, tenacious people who can turn this data, and their knowledge, into insight, strategy and actionsYou’ll be working on the Kaluza platform. This is a technology platform that aims to revolutionise the operating platforms for energy retailers globallyThis platform is being built with globalisation and regionalisation in mind and is the foundation for decarbonisation efforts by Kaluza’s customersWe are looking to transform to an international ready model to help the business take on new challenges and external customersMore specifically, you will join our Data leadership team, working directly to Kaluza’s Head of Data Science & Product, and will be the lead for the Data Platform team as part of thisThe Data Platform team lies at the epicentre of Kaluza’s evolving data & architecture strategy - they build and own the infrastructure, tooling and governance for Kaluza's internal data pipeline, from data ingestion, data cataloguing to data storage and exposing data externallyAs an Engineering Manager, you will be responsible for managing engineers and product analysts who work in our Data Platform team, product or business functions within the wider organisationYou will assist your team in the scoping, planning and delivery of data engineering and analytics engineering projects, assuming accountability for their execution, and flexing your time as you see necessaryYou will introduce thought-leadership on how to deliver excellent analytical and data engineering to the wider practice and contribute to cultivating a positive Kaluza communityIt’s an exciting time currently at Kaluza to contribute to our future state architectural decisions with the opportunity to shape our data estate to represent the best analytical engineering practicesStaff Management: Lead the Data Platform and Analytics Engineering teamsProject Leadership: Scope and lead data engineering projects across the platform, providing technical support where neededTechnical Excellence: Drive the design and building of new data models and production data pipelinesCommunity & Collaboration: Align with data leads across the organisation to improve collaboration and ways of workingOperational Health: Take ownership of security, risk, compliance, and incidents relating to the Data PlatformAgile Delivery: Ensure teams continuously improve quality and velocity through Agile methodologies and recruitmentStakeholder Management: Collaborate with product management to prioritise work based on business impact and urgencyReporting to: Head of Data Science & Products

#J-18808-Ljbffr