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Data Engineer

2 months ago

Sydney, New South Wales, Australia INGRITY Full time
Job Summary

We are seeking a skilled Data Engineer to join our team and provide support for data engineering processes across various customers. The successful candidate will be responsible for data engineering tasks, troubleshooting and resolving data-related issues, ensuring data quality, optimizing data workflows, and providing Level 2 support. This role requires close collaboration with other data engineers and architects to maintain the seamless operation of clients' data infrastructure.

Key Responsibilities
  • Incident Resolution: Investigate and resolve data-related incidents, including issues with data pipelines, ETL processes, and data transformations.
  • Monitoring & Alerts: Monitor system alerts for data jobs and pipelines, resolving issues that arise to ensure timely and accurate data delivery.
  • Data Quality: Ensure the integrity and quality of data by validating data transformations, performing routine checks, and debugging data anomalies.
  • Optimisation: Identify and implement performance improvements in data pipelines and processes.
  • Support Documentation: Maintain comprehensive documentation of common issues, resolutions, and processes to improve future incident response.
  • Collaboration: Work with cross-functional teams, including Data and BI teams, and IT, to ensure alignment and continuity of data solutions and infrastructure.
  • ETL Troubleshooting: Diagnose and resolve issues in ETL workflows, ensuring seamless data flow between systems.
  • Root Cause Analysis: Perform root cause analysis for recurring data issues, proposing and implementing long-term fixes.
  • Stakeholder Communication: Effectively communicate the status of incidents and solutions to stakeholders and business users.
Requirements
  • 2+ years of experience in data engineering, focusing on supporting data workflows and data platforms.
  • Technical Skills:
    • Strong SQL skills for data extraction, transformation, and analysis.
    • Solid experience with data pipeline technologies, particularly in using Azure Data Factory (ADF) to build and manage ETL workflows.
    • Experience with Power BI for data visualization and reporting.
    • Proficient in SQL, including the ability to write complex SQL queries for data extraction, transformation, and analysis.
    • Experience with cloud platforms (e.g., Azure) and associated data services.
    • Understanding of database systems (e.g., MySQL, PostgreSQL, MongoDB).
    • Proficient with version control and CI/CD practices.
  • Problem-Solving: Strong troubleshooting and analytical skills to quickly resolve data issues.
  • Communication: Ability to communicate effectively with technical and non-technical stakeholders.
  • Attention to Detail: High level of accuracy and attention to detail when resolving incidents and ensuring data quality.
  • Education: Bachelor's degree in Computer Science, Data Engineering, or related field (or equivalent experience).