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Data Engineering Associate

On-site work

Publication date: 07/11/2026

Metyis is a global and forward-thinking firm operating across a wide range of industries, developing and delivering AI & Data, Digital Commerce, Marketing & Design solutions and Advisory services. At Metyis, our long-term partnership model brings long-lasting impact and growth to our business partners and clients through extensive execution capabilities. With our team, you can experience a collaborative environment with highly skilled multidisciplinary experts, where everyone has room to build bigger and bolder ideas.

Responsibilities

Diagnose problems, disaggregate issues, develop hypotheses and execute relevant solutions; Undertake processing of structured and unstructured data; Undertake work related to ETL activities; Development of data processing codes for automation & building scalable solutions; Develop and maintain data solutions for clients / projects; Communicate and interact with clients at the executive level; Collaborate with data science, reporting and product development teams

Requirements

3 – 6 years of experience in the field of data engineering; Graduate degree or higher with courses in programming, data analytics; Well-developed Logical Reasoning, Critical Thinking & Problem-Solving abilities; Good programming skill in Python/scala or any scripting language; Good knowledge of SQL is a required; Basic knowledge and understanding of big data; Proven professional experience with Microsoft Azure cloud services is required; Excellent written and oral communication skills in English language is a must

Nice to have

Good to have GIT, CI-CD knowledge; Microsoft Fabric is considered a plus; Strong business acumen and appreciation for business processes is desired

Benefits

Interact with senior stakeholders at our clients on regular basis to drive their business towards impactful change; Become the go-to person for end-to-end data handling, management, and analytics processes; Working with Data Scientists to take data throughout its lifecycle - acquisition, exploration, data cleaning, integration, analysis, interpretation, and visualization; Become part of a fast-growing international and diverse team
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