Strategic Data Engineer Principal

Metyis is growing! We are looking for a Data professional with 8+ years of experience to join our Data Engineering Team. As a Data Engineering Principal, you will lead the design and execution of data engineering projects, while supporting our clients in executing their data strategies.

Requirements

What we offer

• Interact with C-level at our clients on regular basis, to drive their business towards impactful change
• Lead your team in creating new business solutions
• Seize opportunities at the client and at Metyis, in our entrepreneurial environment
• Become part of a fast-growing international and diverse team
• Step-change your career path by becoming a key player in a significant multi-national consulting firm

What you will do

• Independently lead and manage the design and execution of data engineering projects
• Support our clients in executing their data strategies by designing and building operational data platforms: ETL pipelines, data anonymization pipelines, data lakes, near real-time streaming data hubs, web services, training and scoring machine learning model operationalization
• Engineer complete technical solutions to solve concrete business challenges in the areas of digital marketing, eCommerce, Business Intelligence and self-service analytics
• Troubleshoot and QA work done by team members and ensure data engineering best practice
• Collaborate closely with partners, strategy consultants and data scientists in a flat and agile organization where personal initiative is highly valued
• Advise clients on the implementation of effective data governance processes
• Lead knowledge sharing sessions with peers, client prospects and clients
• Communicate and interact with clients at the executive level
• Guide and mentor team members

What you’ll bring

• BSc or MSc in Computer Science, IT or relevant fields desirable
• 8+ years of professional experience in the Data Engineering domain
• Excellent command of both verbal and written English
• The ability to draw inferences from data that is complex and diverse in nature
• Experience designing and setting up modern data lake architectures
• Proven experience in SQL
• Experience using Version Control (e.g. Git), Testing, and CI/CD
• Experience in the automation of data quality monitoring
• Experience of creating data workflows on one of the leading cloud platforms – Azure, AWS, or GCP
• Knowledge of good data governance practices across the data lifecycle