Data Engineering Manager

Metyis is a global and forward-thinking firm operating across a wide range of industries, developing and delivering AI & 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.

Responsibilities

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; 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

Requirements

5-8 years of experience in a similar role with experience in developing and deploying ETL solutions on Azure; 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; Programming languages: Python (PySpark), scripting languages like Bash; 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 (2 or 3-member 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

Nice to have

Basic knowledge of PowerBI; Experience with Airflow, Kubernetes, Great expectations; Master's Degree in a related field; Experience with Data Insights