Data Engineer Principal
Porto, Porto, Portugal
Metyis
We are a dynamic and forward-thinking consultancy firm that operates across a wide range of industries, creating solutions that are tailored to specific needs. We bring long-lasting impact and growth to our partners and clients. We are Metyis....We are looking for a Data Engineering Manager to join our team in Porto. The ideal candidate should have 6-9 years of professional experience in the data engineering domain.
Requirements
What We Offer
- A balanced work environment where you will have autonomy, responsibility, and ownership while working with a vibrant and dynamic team
- A chance to work alongside more junior colleagues, which will allow you to improve your leadership skills, and more senior co-workers who will advise you on your further career development.
- A modern office with everything you need (including food and beverages).
Who We Are
We are Metyis. We are a dynamic and forward-thinking consultancy firm that operates across a wide range of industries, creating solutions that are tailored to specific needs. We bring long-lasting impact and growth to our partners and clients.
With our multidisciplinary teams, we create bold strategies and innovative solutions that are tailored to our client’s needs and help them capitalize on opportunities. Together we strive to bring long-lasting impact and celebrate collective victories.
At Metyis we share an entrepreneurial mindset, a compelling passion to create, and, more importantly, a firm belief in our partnership-driven business model. This is embedded in our culture and safeguarded as we evolve. Our work environment unifies creative problem-solving and strategic thinking. We provide resources to visionaries who understand the direction that which the world is moving. Tomorrow’s world is data-driven. It is digital. It is international.
Become part of the journey, become part of Metyis. Partners for impact.
What You Will Do
- Data Engineers identify data ingestion opportunities that unlock insights, extract them, and organize them 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 the organization 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.
- Organize and lead sharing sessions with peers, customers and functional partners and contribute to evangelizing data engineering practices.
- Guide and mentor new team members.
- Collaborate closely with partners, strategy consultants and data scientists in a flat and agile organization where personal initiative is highly valued.
What You’ll Bring
- BA or MS in Computer Science, Information Technologies, or relevant fields.
- 6-9 years of professional experience in software/data engineering domain.
- Excellent command of English both verbal and written.
- Proven experience in software development and practices and distributed programming with at least one programming language (e.g., R, Python, Java, or C#).
- Proven experience in SQL & NoSQL.
- Experience working setting up data lakes using entire Big Data (e.g., Hadoop, Spark, Presto, Hive, Impala, etc.) and DWH ecosystem.
- Experience using Version Control, Testing and development cycle, preferable git (Gitlab or GitHub).
- Comfortable with Unix OS type systems, Bash, and Linux.
- Experience working on Hyperscalers – Azure, AWS, GCP.
- Experience on data workflows and ETL, Apache Airflow.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Airflow AWS Azure Big Data Computer Science Data management Data pipelines Engineering ETL GCP Git GitHub GitLab Hadoop Linux Machine Learning ML models NoSQL Pipelines Python R Spark SQL Testing
Perks/benefits: Career development
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