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Responsibilities: • Design, implement, and maintain data pipelines for complex enterprise SaaS applications. • Integrate with and manage data from platforms such as Databricks, Snowflake, PowerBI, Tableau, and other ETL systems. • Develop and maintain Python codebases for data ingestion, transformation, and modeling. • Collaborate with backend, product, and analytics teams to deliver business-critical data features. • Optimize data models and storage for performance, scalability, and reliability. • Ensure data quality, integrity, and security across all data flows. • Monitor and troubleshoot data pipelines and participate in on-call support as needed. • Document data architecture, processes, and best practices. Requirements • Experience building and maintaining the data layer for large-scale, enterprise SaaS applications. • Proficient in Python and familiar with data modeling concepts. • Hands-on experience with at least one data platform (Databricks, Snowflake, PowerBI, Tableau, or similar). • Experience with ETL pipeline development and orchestration. • Familiarity with cloud platforms (AWS, Azure, or GCP) and their native data services. Strong understanding of data quality, governance, and security best practices. Soft Skills: • Fast learner, able to pick up new technologies and adapt to evolving requirements. • Clear communicator, capable of working effectively with cross-functional teams. • Ownership mindset; takes responsibility for end-to-end delivery and reliability. Preferred Qualifications: • Experience with multiple data platforms or multi-cloud environments. • Exposure to backend development (TypeScript, GraphQL) or infrastructure automation (Terraform, CI/CD). • Experience in high-growth or product-focused SaaS companies. • Familiarity with AI/ML data pipelines is a plus.