Data Engineer role focused on creating and monitoring data pipelines in an innovative energy company. Collaborate with IT and departments to ensure quality data availability in a hybrid work environment.
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Hybrid Lead Assistant Manager – Data Engineering, Cloud Data Engineering
Posted 2 months ago
About the role
- Lead Assistant Manager overseeing Data Engineering projects with Databricks & Azure Cloud. Managing data pipelines, ensuring data integrity, and supporting insurance business operations.
Responsibilities
- Develop and maintain scalable and efficient data pipelines to ensure seamless data flow across various systems adddress any issues or bottlenecks in existing pipelines.
- Implement robust data checks to ensure the accuracy and integrity of data. Summarize and validate large datasets to ensure they meet quality standards.
- Monitor data jobs for successful completion. Troubleshoot and resolve any issues that arise to minimize downtime and ensure continuity of data processes.
- Regularly review and audit data processes and pipelines to ensure compliance with internal standards and regulatory requirements
- Familiar with working on Agile methodologies - scrum, sprint planning, backlog refinement etc.
Requirements
- 4-9 years experience on Data Engineering role working with Databricks & Azure Cloud technologies.
- Bachelor’s degree in computer science, Information Technology, or related field.
- Strong proficiency in PySpark, Python, SQL.
- Strong experience in data modeling, ETL/ELT pipeline development, and automation
- Proficient in working on Azure cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake etc.
- Experience with data modeling, ETL processes, Delta Lake and data warehousing.
- Experience on Delta Live Tables, Autoloader & Unity Catalog.
- Preferred - Knowledge of the insurance industry and its data requirements.
- Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Excellent problem-solving skills and ability to work under tight deadlines.
- Hands-on experience with performance tuning of data pipelines and workflows
- Excellent communication and problem-solving skills to work effectively with diverse teams
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