Source description
About the role
Design, implement, and maintain scalable data transformation layers and code-first orchestration frameworks to ensure the delivery of high-fidelity, reusable data models
Design and build robust pipelines to ingest data from diverse sources (APIs, logs, relational DBs)
Ensure the reliable and timely execution of all critical data pipelines (ETLs/ELTs) to maintain data integrity and freshness
Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols
Develop and refine a robust semantic layer to facilitate self-service analytics, enabling stakeholders to derive insights without exposure to underlying architectural complexities
Monitor and optimize cloud compute utilization and data model performance to ensure high availability and low-latency reporting during periods of rapid data scaling
Serve as a strategic technical partner to leadership across Product, Engineering, Marketing, and Finance to align data infrastructure with organizational objectives
Become a subject matter expert on the product ecosystem, user behavior, and marketing life cycles to better translate raw data into business value
Serve as a versatile technical resource capable of stepping into the Data Analyst capacity when necessary—performing deep-dive quantitative analysis and building sophisticated visualizations to support executive decision-making
Mentor the data analytics team on advanced technical methodologies to foster a culture of engineering excellence and data autonomy
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