Strategic Data Engineer Principal
Firm
Location
London
Education
Postgraduate degree
Benefits
Competive
Functional areas
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