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Reporting & Analytics Developer / Data Engineer

Summary

Build and maintain data pipelines, ETL jobs, and reporting dashboards using Cloudera, SQL, Python, PySpark, and Tableau.

Reporting & Analytics Developer / Data Engineer

Key Responsibilities

  • Analyse business and data requirements and translate them into technical solutions.

  • Design, develop, and implementdata engineering jobs and reporting solutionsto meet analytical requirements.

  • Develop and maintain data ingestion, transformation, and processing pipelines.

  • Refine data collection and consumption processes by migrating data collection to more efficient channels.

  • Integrate multiple datasets to provide seamless and reliable data access.

  • Build reports, dashboards, and analytical solutions based on user requirements.

  • Develop test plans and test scripts for system testing and support User Acceptance Testing (UAT).

  • Work closely with technical and business teams to ensure smooth deployment and adoption of solutions.

  • Provide production support and troubleshoot complex application and data issues.

  • Ensure smooth operations and adherence to agreed service levels.

  • Participate in Agile/Waterfall project delivery and follow established development methodologies.

  • Use automation to improve development, testing, build, and deployment efficiency.

  • Leverage AI coding and development tools such asGitHub Copilot and Coder AIto support coding, testing, code reviews, refactoring, defect resolution, and documentation.

  • Identify opportunities to adopt AI and automation tools to improve development productivity and code quality.

  • Promote automation, standardisation, and development best practices.

Required Skills & Experience

Must-Have

  • 4+ years of hands‑on experience in Big Data Engineering, preferably within aCloudera Data Platformenvironment.

  • Strong hands‑on experience withCloudera Data Platform.

  • StrongSQL, data modelling, and data analysisskills.

  • Hands‑on experience withPython and PySpark.

  • Hands‑on experience withLinuxand ETL/data integration tools such asInformatica.

  • Strong experience with reporting and data visualisation tools, particularly:

    • SAP BusinessObjects (SAP BO)

    • Tableau

  • Experience developing and maintaining data engineering jobs and ETL pipelines.

  • Good understanding of analytics anddata warehouse implementations.

  • Experience withHive and Impalais preferred.

  • Strong troubleshooting skills, including the ability to diagnose issues across system resources, data pipelines, and application stack traces.

Good to Have

  • Experience withCloudera AI / Machine Learning.

  • Experience withPlotlyand data engineering/AI toolsets.

  • Experience withDenodoor other data virtualisation technologies.

  • Experience with DevOps and deployment processes.

  • Strong scripting experience usingPython and Shell scripting.

  • Experience implementing solutions inhigh-availability, high-performance, and high-security environments.

  • Experience working with hybrid cloud or multi-data‑centre environments.

  • Previous experience implementingAI and automation solutions.

  • Experience with Agile and Waterfall methodologies.

See also

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