Live opening · Posted 20 hours ago
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About the role
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Role Description The Junior Data Engineer role at Ste Word Wide Quincaillerie is a part-time, remote position focused on supporting the design, development, and maintenance of data solutions. In this role, the individual will assist in building and optimizing data pipelines, implementing basic data models, and supporting Extract Transform Load (ETL) processes under the guidance of senior team members. Day-to-day activities include cleaning and organizing data, monitoring data workflows, troubleshooting data issues, and documenting data processes and standards. The role also involves collaborating with analysts and engineers to ensure data is accurate, accessible, and secure, as well as contributing to improvements in data warehousing and reporting. This position offers the opportunity to learn best practices in data engineering while working closely with a distributed, cross-functional team.
Qualifications
Foundational skills in Data Engineering and experience working with data pipelines and data integration tools.
Knowledge of Data Modeling concepts and ability to support the design of structured, scalable data schemas.
Understanding of Extract Transform Load (ETL) processes, including basic data extraction, transformation, and loading techniques.
Exposure to Data Warehousing principles and hands-on experience with data storage and retrieval in structured environments.
Competence in Data Analytics, including querying data and supporting creation of reports and dashboards.
Basic proficiency in SQL and at least one programming language commonly used in data engineering (e.g., Python).
Familiarity with cloud data platforms or tools (e.g., AWS, Azure, Google Cloud) is an advantage.
Strong attention to detail, analytical thinking, and ability to follow established data and documentation standards.
Effective written and verbal communication skills and ability to collaborate in a remote, multicultural team environment.
Relevant coursework or a degree in Computer Science, Data Science, Information Systems, or a related field is preferred.
Work arrangement
Yes
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