Teamlease Digital
Reporting & Analytics Developer / Data Engineer
Skills
2 months ago
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Important information
Contract type:
Permanent
Work mode:
Onsite
Published on:
10 August 2026
What they need
Reporting & Analytics Developer / Data Engineer
Key Responsibilities
- Analyse business and data requirements and translate them into technical solutions.
- Design, develop, and implement data engineering jobs and reporting solutions to 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 as GitHub Copilot and Coder AI to 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 a Cloudera Data Platform environment.
Strong hands-on experience with Cloudera Data Platform.
Strong SQL, data modelling, and data analysis skills.
Hands-on experience with Python and PySpark.
Hands-on experience with Linux and ETL/data integration tools such as Informatica.
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 and data warehouse implementations.
Experience with Hive and Impala is preferred.
Strong troubleshooting skills, including the ability to diagnose issues across system resources, data pipelines, and application stack traces.
Good to Have
- Experience with Cloudera AI / Machine Learning.
- Experience with Plotly and data engineering/AI toolsets.
- Experience with Denodo or other data virtualisation technologies.
- Experience with DevOps and deployment processes.
- Strong scripting experience using Python and Shell scripting.
- Experience implementing solutions in high-availability, high-performance, and high-security environments.
- Experience working with hybrid cloud or multi-data-centre environments.
- Previous experience implementing AI and automation solutions.
- Experience with Agile and Waterfall methodologies.
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