Data Engineer Lead

Job Description

Metyis is a Netherlands based fast-growing international company with a diverse team of over 700+ professionals with a mix of Analytics, Data Science and Technology Team. We are looking for an experienced Data Engineer to join our team with below requirements: Responsibilities: Independently lead & manage execution of data engineering projects Engineer complete technical solutions to solve concrete business challenges in the areas of digital marketing, eCommerce, Business Intelligence and self-service analytics Collect functional and non-functional requirements, consider technical environments, business constraints and enterprise organizations Support our clients in executing their Big 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 models. Troubleshoot and quality check work done by team members Collaborate closely with partners, strategy consultants and data scientists in a flat and agile organization where personal initiative is highly valued Share data engineering knowledge by giving technical trainings Communicate and interact with clients at the executive level Guide and mentor team members Requirements: 7-10 years of professional hands-on experience A broad practice in multiple software engineering fields Experience on managing & leading data engineering / warehousing projects Must have experience on Python, SQL and Distributed programming languages, preferable Spark Experience working on Cloud, Azure is a plus Experience working setting up data lakes using entire Big Data and DWH ecosystem Experience on data workflows and ETL, Apache Airflow is a plus Comfortable with Unix OS type systems, Bash and Linux Basic knowledge of webservices and APIs Basic knowledge of Containers and Docker as platform Experience using Version Control, Testing and development cycle, preferable git (Gitlab or GitHub) Knowledge of security practices Software development practices (Agile) A Strong Focus On Data Processing Object oriented programming Data workflows, monitoring, architecture and security Databases: theory and practice Distributed data processing Concepts of functional programming Enterprise data warehousing, business intelligence and ETL principles Good written and oral communication skills in English language