Posted:5 hours ago|
Platform:
Hybrid
Full Time
0. Create and maintain scalable data pipelines to process large volumes of data efficiently.
0. Implement ETL (Extract, Transform, Load) processes to integrate data from various sources into a unified data platform.
1. Work with technologies such as Apache Hadoop, Spark, Kafka, and other big data tools to integrate and process data.
1. Ensure seamless data flow between different systems and platforms.
2. Optimize and manage data storage solutions, including data lakes and data warehouses.
2. Ensure data is stored in a manner that is both cost-effective and performant.
3. Implement data validation and cleansing processes to ensure high data quality.
3. Monitor data pipelines to detect and resolve data quality issues promptly.
4. Work closely with data scientists, analysts, and other stakeholders to understand their data needs.
4. Translate business requirements into technical specifications and data solutions.
5. Monitor the performance of data pipelines and systems to ensure reliability and efficiency.
5. Troubleshoot and resolve any issues that arise in the data processing workflow.
6. Develop and maintain comprehensive documentation for data engineering processes and systems.
6. Establish and promote best practices for data engineering within the team.
7. Keep up-to-date with the latest trends and advancements in big data technologies and analytics.
7. Evaluate and recommend new tools and technologies to improve data processing and analysis capabilities.
8. Implement and enforce data security measures to protect sensitive information.
8. Ensure compliance with relevant data protection regulations and standards.
9. Develop solutions for real-time data processing and stream analytics to support immediate data insights.
9. Utilize tools and frameworks designed for real-time data handling.
10. Continuously seek opportunities to improve data engineering processes and systems.
10. Participate in code reviews and provide constructive feedback to peers.
Grant Thornton
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