Data Engineer – Data Platform & Analytics

About the role

YPO is building a modern, connected technology ecosystem and needs skilled data engineers to strengthen its analytics foundation. This full‑time remote position supports the company’s growth by designing, building, and maintaining the data platform that powers reporting, analytics, and data products.

Key responsibilities

• Design, develop, and operate ELT/ETL pipelines that ingest data from production systems, third‑party APIs, and SaaS tools into a cloud data warehouse.
• Collaborate with senior engineers to create scalable data models and warehouse structures (e.g., Snowflake, BigQuery, Redshift).
• Translate reporting and analytics requirements from product, analytics, and business teams into robust data models.
• Implement data quality checks, testing, and monitoring to ensure trusted, accurate data.
• Apply modern engineering practices such as version‑controlled transformations (dbt), CI/CD pipelines, and infrastructure‑as‑code.
• Follow data governance standards, including access controls, lineage documentation, and cataloging.

Required profile

• 3–5 years of data engineering experience, preferably in a SaaS or high‑growth technology environment.
• Strong SQL skills and hands‑on experience with a cloud data warehouse (Snowflake, BigQuery, or Redshift).
• Proven ability to build and maintain ELT/ETL pipelines using tools like dbt, Airflow, Boomi, or Mulesoft.
• Solid understanding of dimensional modeling, star schemas, and performance‑focused design.
• Experience with Python (or a comparable language) for pipeline development and automation.
• Working knowledge of cloud platforms (AWS, Azure, or GCP) and exposure to IaC tools such as Terraform.
• Familiarity with streaming technologies (Kafka, Kinesis) and data‑catalog tools is a plus.

Required skills

• Python
• SQL
• Snowflake
• BigQuery
• Redshift
• dbt
• Airflow
• Boomi
• Mulesoft
• AWS
• Azure
• GCP
• Terraform
• Kafka
• Kinesis
• Atlan
• Alation
• dbt docs