Senior Data Engineer: Data Lakehouse & AI Pipelines

Vericast; United States; À distance; USD 130 000 - 150 000; Plein temps

Avantages offerts par ce poste

Medical, dental & vision coverage

401K with match

Paid time off

Résumé du poste

Vericast seeks a Senior Data Engineer to design scalable data pipelines and expand a Data Lakehouse to support marketing and financial institution clients. You will collaborate with analytics, reporting, and data science teams to ensure data quality and availability for AI applications.

The role emphasizes self-direction in an agile environment, working with cross-functional teams to deliver data-driven marketing solutions and improve data models for analytics and AI use cases.

Qualifications

• Bachelor's or Master's degree in Computer Science, IT, or related field.
• 5+ years of Data Engineering experience with ETL and data platforms.
• Experience in FI/Banking/MarTech/Marketing data environments preferred.

Responsabilités

• Develop scalable data pipelines and build integrations for growing data volume and complexity.
• Build a robust Data Lakehouse to support marketing and FI clients, including campaign analysis.
• Collaborate with AI/Analytics teams to improve data models for AI/analytics tools.
• Monitor data quality and ensure availability and accuracy of production data.
• Provide post-deployment support and resolve production issues promptly.

Connaissances

Python

PySpark

Spark

Hadoop

Kafka

Hive

S3

Airflow

Iceberg

Trino

Kubernetes

GitLab

CI/CD

Cloud platforms (AWS/Azure/GCP)

Ranger

Formation

Bachelor's degree in Computer Science, Information Technology, or related field

Master's degree in Computer Science, Information Technology, or related field (preferred)

Outils

Apache Airflow

Trino

Iceberg

Hive

Kubernetes

S3

GitLab

Ranger

Description du poste

Vericast seeks a Senior Data Engineer to design scalable data pipelines and expand a Data Lakehouse to support marketing and financial institution clients. You will collaborate with analytics, reporting, and data science teams to ensure data quality and availability for AI applications.

The role emphasizes self-direction in an agile environment, working with cross-functional teams to deliver data-driven marketing solutions and improve data models for analytics and AI use cases.