01Key Responsibilities
- Perform source-to-target data analysis and data mappings across cloud platforms.
- Collaborate with administrators, developers, data engineers, and analysts to ensure seamless functionality delivery.
- Conduct requirements analysis, coordinating closely with project managers and development teams to drive the project lifecycle.
- Work with Scrum Masters on maintaining product backlogs and assist with sprint planning.
- Design, build, and test data pipelines for both real-time and batch processing to meet project needs.
- Support the development and evolution of the Enterprise Data Platform (EDP) architecture, contributing to the data platform roadmap and architecture initiatives.
- Ensure data quality and integrity across Azure/AWS cloud data environments, focusing on BI and analytical reporting use cases.
- Identify potential risks early and communicate them to stakeholders, helping to develop mitigation plans.
- Build capacity to support data engineering activities as required.
- Follow agile methodologies and DevOps practices to deliver product features and solutions efficiently.
- Maintain adherence to prescribed development processes and best practices.
Skills and Qualifications:
- 10+ years of experience in data engineering or a related field, delivering data solutions in cloud environments.
- Proven experience in Azure or AWS cloud environments, with expertise in Databricks and PySpark.
- Hands-on experience with Cloud BI solutions and familiarity with visualization tools (e.g., Power BI or similar).
- Solid knowledge of agile methodologies and experience with DevOps, DataOps, or DevSecOps practices.
- Proficiency in using PySpark on Databricks for building scalable data processing solutions.
- Excellent written, verbal, and interpersonal communication skills.
- Strong analytical skills with experience in documenting business requirements.
- Exceptional prioritization and proble .
