Senior (Lead) Cloud Data Engineer

Tehtävä

At Sievo, data is everything — we process more than 2% of global GDP in spend, and turning data at that scale into dependable products takes a serious engineering foundation. The team in question is responsible for the platform used to ingest our customers' data - the foundation for Sievo's key data asset. As an Cloud Data Engineer, you will build the tools, libraries, data schemas, processes, and best practices that our Data Engineers use to build customer-specific ELT pipelines. We lay the foundation for processing large datasets at scale, enabling reliable extraction and transformation of o… This role sits at the intersection of data engineering and software engineering. You will design and build an ELT platform that supports the various needs of our data pipelines, data products, and Data Engineers working with it. You know how to build and manage solid data pipelines, can design the environments and infrastructure they require, and apply solid software engineering practices — version control, testing, automation, and reproducibility — so the products built on top are dependable. Think of it as a data engineer with a product-development mindset and the engineering rigor of a soft… You will work closely with data engineers, software engineers, and other product teams — gathering requirements, making sensible technical trade-offs, and sharing ownership of the platform you help build. This is not a single-project role: in the longer term, the work enables many teams, giving you a hand in shaping Sievo's data-driven future as a whole. Build standard Azure Databricks solutions for our integration pipelines between customer solutions and Sievo cloud Own and improve ELT products built for extraction, transformation, and loading data to the Sievo's Procurement Data Schema Apply software engineering practices throughout: Git-based version control, CI/CD-style workflows, automated testing, and reproducible, production-quality code Proactively suggest and implement improvements to reduce manual work, increase testing, scalability, robustness, and availability of data systems Improve tooling used by data engineers to access, transform, and validate data Develop reproducible environments and cloud resources — permissions, deployment patterns, infrastructure-as-code, security, scalability, and cost efficiency Build common monitoring, data quality checks, and validations so that our data remains trustworthy and understandable Gather technical requirements from internal stakeholders, clearly communicate trade-offs, and work with the team to take deliverables through to production Troubleshoot platform and integration issues, fixing root causes rather than symptoms You'll be building the backbone of Sievo's key data asset — one whose scope is set to grow. You'll have the autonomy to shape the architecture, choose the right tools, and set the engineering standards, working directly with engineering and data engineering to turn data into dependable, production-grade capabilities.