Data Engineer Middle/Senior

Job Description

This role is ideal for an experienced Data Engineer who enjoys designing and implementing data pipelines and working closely with cross-functional teams to deliver robust, scalable data platforms.

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Requirements:

• Bachelor’s degree in Computer Science, Information Technology, or a related field;

• 3+ years of experience in Data Engineering;

• At least 1 year of hands-on experience developing data pipelines using any of AWS/Azure/CPG, PySpark, and Python;

• Strong proficiency in SQL;

• Familiarity with data lake environments, including handling both structured and unstructured data;

• Knowledge of data warehouse, data lake, and enterprise big data platforms;

• Upper-Intermediate English skills (verbal and written);

• Strong communication and persuasion skills;

• Capability to effectively engage with both technical and business stakeholders;

• Proven ability to work independently and cooperatively as part of an international project team.

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Responsibilities:

• Plan, build, and implement data solutions;

• Groom and estimate user requirements, and identify new features;

• Analyze data sources, design and develop pipelines to ingest data;

• Design and create ETL processes to supply the data warehouse;

• Preprocess structured and unstructured data, and create queries in databases;

• Establish and maintain technical specification documentation.  

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What We Offer:

• Competitive salary;

• 100% remote opportunity;

• Opportunities for professional growth and advancement;

• A cooperative and innovative work environment;

• 20 days of paid vacation, 15 paid days of sick leave with a doctor’s note, and 5 days of paid sick leave without a doctor’s note;

• Medical insurance coverage for employees, with optional family insurance at a corporate rate;

• Support for participation in professional development opportunities (webinars, conferences, trainings, etc.);

• Regular team-building activities and bi-annual company-wide events;

• Flexible work environments, including in-office, remote, or hybrid options based on employee preference and manager approval.

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