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.