Responsibilities
- Design, build, and sustain ELT and ETL workflows that handle large-scale data for analytics
- Develop sophisticated data processing systems with strong monitoring to guarantee data accuracy, timeliness, and dependability
- Create and enhance data models and semantic layers to empower user-driven analysis and detailed reporting
- Construct visual dashboards and reports that meet analytical needs
- Convert intricate business and data requirements into high-performance, expandable data solutions
- Follow best practices in version control, documentation, continuous integration and deployment, infrastructure as code, and data governance
- Engage in code reviews, suggest architectural enhancements, and support ongoing team improvements
- Collaborate with data engineers, database administrators, managers, and business teams to deliver impactful data products
- Offer technical leadership, informal mentoring, and assistance to strengthen team expertise
- Explain technical choices, risks, and suggestions clearly to both technical and non-technical stakeholders
- Improve the efficiency, cost, and scalability of data pipelines and data warehouse systems
- Assess, test, and advocate for new tools, frameworks, and architectural approaches to advance the data platform
- Support data monitoring, incident resolution, and deep analysis of data-related issues
- Develop data products ready for AI applications, ensuring compatibility with natural language processing, predictive modeling, and other AI technologies
Work Arrangement
Hybrid
Other
#LI-Hybrid
