Data Operations Engineer(DBT, Snowflake, Terraform, Apache, Python, AWS, SQL) Fulltime - Remote - Night Shift - 8+ Years needed

Role: Data Operations Engineer

What You’ll Do

Operations Support

● Monitor and triage production data pipelines, ingestion jobs, and transformation workflows (e.g. dbt, Snowflake tasks)

● Manage and resolve data incidents and operational issues, working cross-functionally with platform, data, and analytics teams

● Develop and maintain internal tools/scripts for observability, diagnostics, and automation of data workflows

● Participate in on-call rotations to support platform uptime and SLAs

Data Platform Engineering Support

● Help manage infrastructure-as-code configurations (e.g., Terraform for Snowflake, AWS, Airflow)

● Support user onboarding, RBAC permissioning, and account provisioning across data platforms

● Assist with schema and pipeline changes, versioning, and documentation

● Assist with setting up monitoring on new pipelines in metaplane

Data & Analytics Engineering Support

● Diagnosing model failures and upstream data issues

● Collaborate with analytics teams to validate data freshness, quality, and lineage

● Coordinate and perform backfills, schema adjustments, and reprocessing when needed

● Manage operational aspects of source ingestion (e.g., REST APIs, batch jobs, database replication, kafka)

(confirm the writeup with Jason Prentice)

What We’re Looking For

Required Qualifications

● At least 2–4 years of experience in data engineering, DevOps, or data operations roles

● Solid understanding of modern data stack components (Snowflake, dbt, Airflow, Fivetran, cloud storage)

● Proficiency with SQL and comfort debugging data transformations or analytic queries

● Basic scripting/programming skills (e.g., Python, Bash) for automation and tooling

● Familiarity with version control (Git) and CI/CD pipelines for data projects

● Strong troubleshooting and communication skills — you enjoy helping others and resolving issues

● Experience with infrastructure-as-code (Terraform, CloudFormation)

● Familiarity with observability tools such as datadog

● Exposure to data governance tools and concepts (e.g., data catalogs, lineage, access control)

● Understanding of ELT best practices and schema evolution in distributed data systems