Data Ops Engineer

Overview

DataOps Engineer responsible for operationalizing, automating, and improving reliability of 2K’s data ecosystem using DevOps practices for data engineering.

What you'll do

• Design and maintain scalable ETL/ELT pipelines to ingest and transform data into central data warehouses.
• Implement and manage CI/CD pipelines for data assets, including automated extraction, testing, and deployment.
• Use Infrastructure-as-Code to manage and version cloud infrastructure and maintain environment parity.
• Monitor pipeline health and data quality, and build automated alerting systems to resolve bottlenecks.
• Implement data security and access controls and support GDPR and CCPA compliance for pipelines.
• Collaborate with Data Scientists and Analysts to enable data availability and support modeling/insights.

What you'll need

• 6+ years of professional experience in DataOps, Data Engineering, or DevOps with focus on large-scale data systems.
• Expert-level Python and SQL skills.
• Hands-on experience with orchestration tools such as Apache Airflow, Mage, or Prefect and transformation tools such as dbt.
• Deep experience with AWS (or GCP/Azure) and containerization technologies such as Docker and Kubernetes.
• Proficiency with Git for version control and Terraform for infrastructure management.
• Advanced knowledge of modern data warehouse/lakehouse environments such as Snowflake and Databricks.

Details

• Role is tagged with "#LI-Onsite".