POSITION SUMMARY

The Data Operations Engineer plays a crucial role in enabling data-driven decision-making across the organization. This individual will work closely with stakeholders to deliver and support business operations, focusing on democratizing data and building robust analytics solutions. The Data Operations Engineer will develop data solutions, enhance internal analytics platforms, and streamline processes to drive efficiency.
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• Serve as an expert for Data Analytics and Reporting:
• BI systems and reporting: Enablement, compliance, development, and maintenance (PowerBI, Qlik, Cognos, MicroStrategy).
• ETL tools: Enablement, compliance, development, and maintenance (Alteryx, Python, Fivetran, Rivery).
• Data warehousing: Design, development, and maintenance of data models and structures (Snowflake, Redshift, Postgres).
• Data pipelines: Build, monitor, and optimize data pipelines for efficient data flow (Airflow, AWS Step Functions, AWS Lambda).
• Enable cross-functional collaboration:
• Promote a data-driven culture by educating and supporting teams in using analytics tools and data effectively.
• Improve operational efficiencies:
• Democratize data access to enable self-service analytics and data-driven insights.
• Identify and implement cost-saving opportunities related to data infrastructure and processes.
• Maintain and enhance a centralized repository of data sources, processes, and data flows.
• Optimize data processes to reduce complexity and improve performance.
• Document data workflows and processes for business continuity and transparency.
• Adhere to data governance best practices.
• Identify and address technical debt within data pipelines and systems.
• Share knowledge and best practices for efficient code and architectural principles.
• Design end-to-end solutions that deliver timely and accurate data for business consumption.
• Manage and democratize data:
• Develop and maintain workflows to prepare and transform data for analysis.
• Transform data into actionable insights for business stakeholders.
• Understand data relationships, flows, and their impact on key performance indicators (KPIs).
• Develop and maintain operational dashboards to monitor business performance.
• Enhance and expand the data warehouse and pipelines to support the organization’s analytical maturity.
• Foster a data-driven community within the organization by sharing knowledge and promoting data reuse.
• Strategic planning and support:
• Contribute to the analytical framework for strategic decision-making across business functions.
• Ensure successful data operations:
• Deliver projects based on priorities set for the Data Analytics team.
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