Remote Data Engineer — Snowflake & Airflow

Unavailable; Córdoba; Híbrido; ARS 181.094.000 - 271.641.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Comprehensive benefits

Flexible work environment

Wellness and community days

Recognition for contributions

Global collaboration

Descripción de la vacante

Proofpoint is seeking a Staff Data Engineer to join our Data Platform team. In this senior individual-contributor role you will design, build, and operate the large-scale data infrastructure that underpins Proofpoint's cybersecurity products and analytics.

You will lead data pipelines on AWS (S3, Glue, Athena), implement data quality and governance, and mentor junior engineers while collaborating with data scientists and product managers to translate requirements into robust data models.

Formación

• 8+ years of professional software or data engineering experience, with 4+ years on cloud data platforms.
• ,
• Strong Python and SQL skills with production-grade data pipelines.
• Excellent communication and mentoring abilities.
• Bachelor's degree in CS/Engineering or related field.

Responsabilidades

• Design, build, and operate large-scale data pipelines on AWS.
• Maintain data lake architecture on S3 with proper cataloging and formats.
• Enforce data quality, governance, and incident response.
• Lead design reviews and mentor junior engineers.

Conocimientos

Python programming

SQL

Communication skills

Mentoring/leadership

CI/CD for data

Design reviews

Educación

Bachelor's degree in Computer Science/Engineering

Herramientas

AWS Glue

Amazon S3

Apache Spark / PySpark

Terraform/CDK

Descripción del empleo

Position Overview

Proofpoint is looking for a Staff Data Engineer to join our growing Data Platform team. In this senior individual‑contributor role you will design, build, and operate the large‑scale data infrastructure that underpins Proofpoint's cybersecurity products and analytics.

• Design and implement scalable, reliable data pipelines using AWS Glue (PySpark and Glue Studio) to ingest and transform petabyte‑scale datasets stored in Amazon S3.
• Build and maintain our cloud data lake architecture on S3, defining partition strategies, file formats (Parquet, ORC, Delta), and data‑catalog schemas in AWS Glue Data Catalog.
• Establish and enforce data quality standards – implement validation frameworks, anomaly detection, and SLA‑driven alerting to ensure data reliability.
• Define and drive engineering best practices: code reviews, CI/CD for data pipelines, Infrastructure‑as‑Code (Terraform/CDK), and DataOps principles.
• Serve as a technical leader and mentor – conduct design reviews, guide junior engineers, and influence the team's technical roadmap.
• Collaborate closely with data scientists, ML engineers, and product managers to translate business requirements into robust data models and pipeline specifications.
• Champion data governance, lineage tracking, and privacy‑by‑design principles across all data assets.
• Troubleshoot and resolve production incidents, perform root‑cause analysis, and drive preventive improvements.
• Contribute to architecture decision records (ADRs) and technical documentation.

What You Bring to the Team

• 8+ years of professional software or data engineering experience, with at least 4 years focused on cloud data platforms.
• Deep expertise with AWS data services: S3 (lifecycle policies, event notifications, encryption), AWS Glue (ETL jobs, Crawlers, Data Catalog, Glue Studio), and Amazon Athena (query optimization, workgroups, federated queries).
• Strong Python programming skills; proficiency writing production‑grade PySpark or Spark (Scala) for large‑scale data transformation.
• Solid SQL fundamentals – ability to write and tune complex analytical queries.
• Excellent communication skills – able to present technical trade‑offs clearly to both engineering and non‑engineering stakeholders.
• Proven experience mentoring engineers and leading technical design discussions.
• Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).

Nice to Have

• Experience with real‑time / streaming data processing using Apache Kafka, Amazon Kinesis, or AWS Glue Streaming ETL.
• Familiarity with AWS Lake Formation for fine‑grained access control and data governance.
• Knowledge of Amazon Redshift or other cloud data warehouses.
• Experience with data quality frameworks (Great Expectations, Deequ, or similar).
• Background in cybersecurity, threat intelligence, or security analytics data.
• AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect certification.
• Contributions to open‑source data engineering projects or publications.

Benefits

• Competitive compensation
• Comprehensive benefits
• Career success on your terms
• Flexible work environment
• Annual wellness and community outreach days
• Always on recognition for your contributions
• Global collaboration and networking opportunities

Culture and Inclusion

Our culture is rooted in values that inspire belonging, empower purpose and drive success – every day, for everyone.

We encourage applications from individuals of all backgrounds, experiences, and perspectives. If you need accommodation during the application or interview process, please reach out to .

Equal Opportunity

Proofpoint is an equal opportunity employer, we hire without consideration to race, religion, creed, color, national origin, age, gender, sexual orientation, marital status, veteran status or disability.