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Job Description & How to Apply Below
We are hiring a ๐๐๐ญ๐ ๐๐ง๐ ๐ข๐ง๐๐๐ซ for a technology and data opportunity in ๐๐๐ฎ ๐๐ก๐๐๐ข
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This role is ideal for a hands-on engineer who enjoys working behind the scenes to make data dependable, accessible, and ready for use. You will help strengthen the movement of data across different systems while supporting the quality and reliability of the wider data environment.
Key Responsibilities- Keep critical data flows reliable by monitoring integrations, investigating interruptions, and resolving issues affecting the availability, freshness, or accuracy of data.
- Work with technical and business teams to bring additional data sources into the environment, translating source structures and requirements into stable integration solutions.
- Strengthen the quality of incoming data through validation, testing, reconciliation, and analysis before information is made available for downstream use.
- Contribute to the design and maintenance of practical data models that support evolving analytical and operational requirements.
- Develop and enhance automated data pipelines using appropriate ETL/ELT methods, SQL, Python, APIs, database connectivity, and secure transfer mechanisms.
- Support a well-controlled engineering environment by improving deployment processes, maintaining technical documentation, and applying appropriate data security and access practices.
- Hands-on proficiency with SQL and Python
, together with practical experience developing or supporting data pipelines and integration workflows. - 3+ years of experience in data engineering, data integration, backend data processing, or a related technical discipline.
- Good understanding of ETL/ELT concepts, APIs, database interfaces, secure file exchange, and connecting information across different source systems.
- Experience working with data models, validation rules, quality controls, and troubleshooting data issues across interconnected environments.
- Familiarity with automated testing and deployment practices, as well as the basic networking and security considerations involved in system-to-system data exchange.
- Bachelorโs degree in Computer Science, Information Systems, Data Engineering, or a related field; broader exposure to analytics, big data, or complex multi-source environments would be beneficial.
This opportunity gives you exposure to end-to-end data engineering challenges, from bringing new sources into an established environment to improving pipeline reliability, data quality, and the technical foundations that support analytics.
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