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    Open rolePosted 5 November 2026

    Data Engineer

    Employment Type: Full-time, B2B, Remote

    • Work arrangement: Fully remote

    About the role

    Expected Start Date: December 2026 Duration: 3 months

    Job Description

    The Data Engineer will be responsible for supporting the design, development, and implementation of a cloud-based data platform leveraging Amazon Web Services (AWS) and Snowflake.

    The role involves developing and maintaining data pipelines, implementing ETL/ELT processes, automating data ingestion, and ensuring data accuracy, consistency, and reliability.

    The position requires collaboration with back-end engineers, BI specialists, and the internal product development team to ensure effective data integration and availability for analytics, reporting, and business intelligence purposes.

    Key Responsibilities

    • Contribute to the design and implementation of the data platform architecture.

    • Develop, implement, and maintain ETL/ELT processes.

    • Design, build, and manage scalable data pipelines using AWS and Snowflake.

    • Automate data ingestion from multiple sources.

    • Implement data transformation and processing workflows.

    • Develop data validation mechanisms to ensure data accuracy and consistency.

    • Implement error-handling mechanisms and troubleshoot data pipeline failures.

    • Monitor and optimize data pipelines for performance, reliability, and scalability.

    • Support the integration of different data sources into the central data platform.

    • Collaborate with BI specialists to ensure data is structured and accessible for reporting and analytics.

    • Maintain technical documentation related to data architecture, ingestion, and transformation processes.

    Requirements

    Required Qualifications and Technical Skills

    • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.

    • Proven experience in data engineering or data platform development.

    • Knowledge and practical experience with AWS cloud services.

    • Experience with Snowflake data warehousing.

    • Understanding of ETL/ELT processes and data pipeline architecture.

    • Experience with automated data ingestion and transformation.

    • Knowledge of data validation, quality assurance, and error-handling practices.

    • Familiarity with SQL and database management.

    • Understanding of data integration and cloud-based data architectures.

    • Strong analytical and problem-solving skills.

    How it works for you

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    2. Record your interviews

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    3. A short live call

      Once your interviews pass, we meet you on a quick video call.

    4. Matched to client work

      We put you forward for every role that fits, not only the one you applied to, and tell you when there is no current match.

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