Senior Data Platform Engineer ID92207

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you

ABOUT THE ROLE

We are looking for a Senior Data Engineer to operate and improve a Snowflake-based enterprise data platform in a regulated healthcare environment.

WHAT YOU WILL DO

- Provide senior technical ownership for the Data Platform service tower during the LatAm coverage window, including day-to-day operations, complex troubleshooting, and L2/L3 escalation.

- Operate and improve Snowflake production and non-production environments, including warehouse configuration and sizing, performance and consumption monitoring, object lifecycle, environment hygiene, and support for production changes.

- Administer data access within established controls, including users, roles, service accounts, secrets, and credential rotation, while maintaining least-privilege and audit-ready practices.

- Operate and improve data ingestion across Fivetran, HVR where applicable, and custom pipelines, including connector configuration, scheduling, source onboarding, schema-change coordination, failure recovery, backfills, and dependency management.

- Design, build, and maintain reliable pipelines and dbt models across RAW, CURATED, and CONSUMPTION layers, with appropriate testing, documentation, lineage, version control, and CI/CD practices.

- Support AWS S3 data-lake operations, including raw and landing-zone workflows, lifecycle and retention controls, access patterns, logging, ingestion failures, and coordination with downstream Snowflake workloads.

- Support Argo Workflows and Kubernetes-hosted data workloads in close coordination with the Cloud / DevOps team, including scheduling, troubleshooting, deployment, recovery, and capacity dependencies.

- Define and improve data quality and observability standards, including freshness, zero-row, row-count growth, null, duplicate, schema-drift, and referential-integrity checks.

- Expand end-to-end monitoring and lineage using tools such as SYNQ, dbt, Snowflake audit data, Splunk, and the agreed alerting stack, linking actionable alerts to evidence and runbooks.

- Lead or support major data incidents, root-cause analysis, post-incident reviews, and preventive actions across ingestion, orchestration, Snowflake, and downstream Tableau dependencies.

- Support Tableau Cloud operations where upstream data, connectivity, permissions, extracts, or refresh failures require Data Platform investigation.

- Identify and deliver standardization, automation, reliability, performance, and cost improvements, including migration of suitable legacy or custom extraction patterns toward agreed golden paths.

- Execute work through controlled incident, request, access, change, and release processes using established service-management workflows.

- Create and maintain runbooks, operating procedures, architecture context, ownership information, recovery procedures, and knowledge-transfer materials.

- Mentor Middle-level engineers, review technical work, improve team practices, and ensure effective handoffs across the distributed service team.

- Participate in the Data Platform on-call rotation for critical incidents outside staffed service hours.

MUST HAVES

- 5+ years of professional experience in Data Engineering or Data Platform Engineering .

- Strong hands-on experience operating and developing solutions on Snowflake , including data-layer design, warehouse performance, access patterns, and production troubleshooting.

- Advanced SQL skills and strong experience with dbt for transformation, testing, documentation, lineage, and controlled deployment.

- Experience operating managed ingestion tools such as Fivetran or HVR and supporting custom data-ingestion pipelines.

- Hands-on experience with AWS data services , particularly S3 and event-driven or file-based ingestion patterns.

- Experience orchestrating and troubleshooting data workloads with Argo Workflows on Kubernetes , or comparable workflow-orchestration technologies.

- Proficiency in Python or a comparable language for data engineering, automation, and operational tooling.

- Strong understanding of data modeling, pipeline dependencie