Data Engineering Lead

Metyis is growing! We are looking for a Data Engineering Lead with 5-8 years of experience to join our global Data and Analytics team at our Digital Campus in Porto. Who we are Metyis is a global and forward-thinking firm operating across a wide range of industries, developing and delivering Big Data, Digital Commerce, Marketing & Design solutions and Advisory services. At Metyis, our long-term partnership model brings long-lasting impact and growth to our business partners and clients through extensive execution capabilities. With our team, you can experience a collaborative environment with highly skilled multidisciplinary experts, where everyone has room to build bigger and bolder ideas. Being part of Metyis means you can speak your mind and be creative with your knowledge. Imagine the things you can achieve with a team that encourages you to be the best version of yourself. We are Metyis. Partners for Impact. What we offer Interact with senior stakeholders at our clients on regular basis to drive their business towards impactful change. Become the go-to person for end-to-end data handling, management, and analytics processes. Lead your team in creating the pipeline for Data management, data visualization, and analytics products, including automated services, and APIs. Working with Data Scientists to take data throughout its lifecycle - acquisition, exploration, data cleaning, integration, analysis, interpretation, and visualization. Become part of a fast-growing international and diverse team. What you’ll do Lead, influence & implement the technical roadmap of our clients, in light of overall technology and architecture roadmaps. Be responsible for the Architecture, making sure that technical and non-technical components work together in the product to deliver the customer needs. Lead and Develop the digital development and operations using Python, Spark, RESTful API, and Microsoft Azure Cloud, ideally with some Data Insights experience. Steer the technical excellence of the application and consistency with relevant digital frameworks, best practices, and standards. Coach and enable other product team members to deliver best-in-class products. Deliver data platforms, data insights and with the collaboration of the data science team – data products, such as recommendation systems, data lakes/hubs, data insights and dashboards. Lead project activities and will be responsible for the evaluation of business needs and objectives in collaboration with the project team and other stakeholders. What you’ll bring 5 – 8 years of experience in a similar role with experience in developing and deploying ETL solutions on Azure, GCP or AWS. Solid knowledge of data warehousing principles, concepts, and best practices (e.g. ODS, data marts, data lakes, data vault, 3NF). Good understanding of common platforms and practices regarding digital development; Cloud-based setups, Advanced Analytics and computing environments, and GitHub (or similar) and CI/CD workflows. Experience in setting up automated testing frameworks including unit tests, integration tests. Understanding of modern cloud-based architecture (Lambda & Kappa architectures). Advanced SQL, data transformation, and data profiling skills. Experience in building production ETL/ELT pipelines at scale. Data governance experience. 3 – 5 years of hands-on experience with Azure: Data Factory, Databricks, Synapse (DWH), Azure Functions, App logic, and other data analytics services, including streaming. Experience with Airflow, Kubernetes, Great expectations is a plus. Programming languages: Python (PySpark), scripting languages like Bash. Basic knowledge of PowerBI is a plus. Customer-centric, passionate about delivering great digital products and services. Demonstrating true engineering craftsmanship mindset. Passionate about continuous improvement and working collaboratively. Strong problem-solving skills coupled with the ability to convey designs and ideas to a wider audience. People Management experience (at least 2 members team). Experience in service consulting and stakeholder management. Comfortable with ambiguity, highly autonomous. A Bachelor's Degree in Computer Science, Mathematics, Economics, Engineering, Operations Research. Statistics, Business or other related technical disciplines (Master's Degree is a plus).