Description

You will build and maintain data pipelines and foundational datasets to support analytics, modeling, and product needs.

Responsibilities

• Design and build database architectures for massive, complex datasets while balancing computational load and cost.
• Collaborate with data science, machine learning, and engineering teams to improve instrumentation accuracy and reliability.
• Develop scalable data quality audits, including alerting and anomaly detection systems.
• Create scalable dashboards and reports to enable data-driven decision making.
• Optimize ETL and dashboard performance to improve efficiency and reduce costs.

Required Skills

• 5+ years of professional experience.
• 3+ years building production data pipelines with high volumes of consumer data.
• 3+ years designing and maintaining data models from structured and unstructured sources.
• 3+ years of experience with SQL, Python, and PySpark.
• 3+ years of experience with public cloud platforms (AWS, Microsoft Azure, or Google Cloud).
• 3+ years of experience with NoSQL implementations such as DynamoDB or CosmosDB.
• Experience developing and maintaining CI/CD pipelines for Databricks using Azure DevOps.
• Experience implementing data quality audits for datasets containing billions of rows.
• Strong stakeholder management skills for working in ambiguous environments.

Key Skills

Education

Any Graduate