Zipporin is seeking an experienced Data Pipeline Automation Engineer to spearhead the evolution and resilience of our data infrastructure. In this 100% remote role, you will champion modern DataOps methodologies, building automated, self-healing pipelines and robust CI/CD frameworks that ensure continuous data delivery and enterprise-grade reliability.
Key Responsibilities:
- Design, build, and maintain automated ETL/ELT data pipelines using Python, SQL, and Apache Airflow.
- Establish DataOps practices, including automated testing, schema verification, and continuous deployment workflows.
- Provision and standardize scalable cloud data infrastructure using Infrastructure as Code (IaC) with Terraform.
- Implement advanced observability, logging, and automated alerting to guarantee pipeline health and rapid incident recovery.
- Partner with analytics engineers and data scientists to streamline data access, reduce pipeline latency, and optimize query performance.
Requirements:
- 4+ years of dedicated experience in data engineering, data infrastructure, or DataOps environments.
- Demonstrated expertise with workflow orchestrators (Apache Airflow, Prefect, or Dagster) and robust Python programming.
- Strong experience implementing CI/CD pipelines (GitHub Actions, GitLab CI) and managing cloud infrastructure via Terraform.
- Hands-on experience with modern cloud data warehousing solutions such as Snowflake, BigQuery, or Databricks.
- Proven ability to independently manage end-to-end automation projects in a fast-paced, fully remote team.