Proofpoint is looking to enhance its data pipeline and leverage advanced data analytics to support strategic initiatives for customer success, including Customer 360, automated product health diagnostics, predictive churn models, and Power BI dashboards.
Requirements
- Advanced knowledge of SQL and Python for data manipulation, pipeline automation, and business logic implementation.
- Experience with modern data platforms (Snowflake, Redshift, BigQuery, Databricks, or equivalent).
- Experience with AWS infrastructure (e.g., S3, Lamda, Glue, Redshift).
Responsibilities
- Collaborate closely with Engineering - Business Applications team to ensure a robust data pipeline is in place in our AWS infrastructure (e.g., S3, Lamda, Glue, Redshift)
- Partner with Customer Success subject matter experts to define data requirements and transformation logic
- Use SQL, Python, and other data processing languages to implement transformation logic to produce outputs that enable data-driven customer success initiatives
- Develop scalable, reusable code for reduce delivery time for future initiatives
- Ensure data quality, consistency, and scalability across large, complex datasets.
Other
- 5+ years of experience in data engineering / analytics, preferably in a SaaS or technology company.
- Extensive hands-on use of Excel
- Strong collaboration skills with both technical and non-technical stakeholders.
- Ability to work on multiple projects at once
- Ownership mentality – proactively solving problems and assuming accountability for results
- Proven ability to thrive in a high-growth, fast-paced, dynamic environment.
