Data Engineering Associate
Big data and analytics

Who we are

We are Metyis, a forward-thinking, global company that collaborates with business partners and clients to create and implement the capacities and capabilities required to improve future performance. We operate across a wide range of industries, and with our embedded partnership model we commit to driving sustainable growth for industry-leading organisations, elevating their potential with a long-term vision.

At Metyis, we develop integrated solutions that enable growth by working within our business partners’ organisations with diverse and multidisciplinary teams. This collaborative environment allows Metyis to build strategies and execute them through an ecosystem that combines Big Data solutions, Digital Commerce solutions, Marketing & Design solutions, and Advisory services.

Our teams are set up so that you have plenty of room to build bigger and bolder ideas by speaking your mind and being creative with your knowledge. Imagine the things you could achieve with a multidisciplinary team that encourages you to be the best version of yourself.

We are Metyis. Partners for Impact.

What we offer 

  • Opportunity to accelerate the pace of digitalisation & e-commerce growth through advanced technology, business intelligence and analytics
  • Driving high-impact insights enhancing decision making across the entire organisation
  • Driving brand equity and digital sales through enhanced digital experiences
  • Interaction with senior business and e-commerce leaders on regular basis to drive their business towards impactful change
  • Become part of a fast growing international and diverse team

What you will do  

  • Data Engineers identify data ingestion opportunities that unlock insights, extract it and organize it in a way that’s widely available, scalable and that answers any critical use case. You will also team up with data scientists to ensure a constant feed of fresh data into machine learning models and support on the organisation of any performance related metrics and data
  • Support our clients in executing their Big Data strategies by designing and building reusable components, frameworks and libraries at scale to support analytics products
  • Design, build and launch extremely efficient and reliable data pipelines to move data across several platforms including data warehouses, data lakes, operational systems, online services and real-time systems
  • Anticipate, identify and solve issues concerning data management to improve data quality
  • Organise and lead sharing sessions with peers, customers and functional partners and contribute to evangelising data engineering practices
  • Guide and mentor new team members  
  • Collaborate closely with partners, strategy consultants and data scientists in a flat and agile organisation where personal initiative is highly valued

What you’ll bring  

  •  3+ years of work experience.
  • Proven experience in software development and practices with at least one programming language (e.g. Python, Java or C#). 
  • Proven experience in SQL. 
  • Proven experience analyzing and modelling data to discover opportunities and address gaps. 
  • Proven experience in building data pipelines within data ingestion projects using data flows management platforms (e.g. Airflow, Microsoft SSIS, Google Cloud Composer, AWS Step Functions, Azure Data Factory). 
  • Ability to work in the English language with strong written and oral communication skills  
  • Proven experience with cloud platforms (e.g. Azure, Google Cloud Platform or AWS Webservices) 
  • Proven experience querying massive datasets using Spark, Presto, Hive, Impala, etc. 
  • Proven experience with more than one coding language. 
  • Proven experience with designing and implementing real-time pipelines. 
  • Proven experience with SQL performance tuning and E2E process optimization. 
  • Proven experience with anomaly/outlier detection. 
  • Proven experience with notebook-based Data Science workflow. 
  • Proven experience to travel for business meetings, as required.
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