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

Role: Data Operations EngineerWhat You’ll DoOperations 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 SLAsData 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 metaplaneData & 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 ForRequired 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