Job Description

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 dependencies, schema evolution, backfills, data validation, and production data quality.

- Experience with observability, logging, alerting, and incident-management practices for production data platforms.

- Demonstrated ability to lead complex incident resolution, perform root-cause analysis, and convert findings into preventive improvements.

- Ability to make well-reasoned technical decisions, identify tradeoffs, estimate work, and guide improvements across a complex platform.

- Experience mentoring engineers and collaborating effectively with Cloud / DevOps, Analytics, Security, Governance, and business stakeholders.

- Strong written and verbal English communication skills, with the ability to work directly with client stakeholders.

- Full availability to work from 9:00 AM to 6:00 PM Pacific Time and participate in an agreed on-call rotation.

NICE TO HAVES

- Hands-on experience with a data-specific observability platform.

- Experience supporting Tableau Cloud administration, data-source connectivity, extracts, scheduled refreshes, or production dashboard dependencies.

- Familiarity with Snowflake cost optimization, audit logging, tasks, stored procedures,



and environment rationalization.

- Experience migrating legacy ingestion or orchestration patterns such as Boomi or AWS Data Pipeline to modern managed or Kubernetes-based solutions.

- Experience with Terraform, CI/CD pipelines, and Infrastructure as Code practices supporting data platforms.

- Experience with service-management and change-control tools such as Freshservice and Jira.

- Familiarity with HIPAA, GDPR, FDA-related controls, least-privilege access, separation of duties, and audit-ready operational practices.

PERKS AND BENEFITS

- Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.

- Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.

- A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.

- Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Requirements
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 dependencies, schema evolution, backfills, data validation, and production data quality. Experience with observability, logging, alerting, and incident-management practices for production data platforms. Demonstrated ability to lead complex incident resolution, perform root-cause analysis, and convert findings into preventive improvements. Ability to make well-reasoned technical decisions, identify tradeoffs, estimate work, and guide improvements across a complex platform. Experience mentoring engineers and collaborating effectively with Cloud / DevOps, Analytics, Security, Governance, and business stakeholders. Strong written and verbal English communication skills, with the ability to work directly with client stakeholders. Availability to work from 9:00 AM to 6:00 PM Pacific Time and participate in an agreed on-call rotation.

📌 Senior Data Platform Engineer (Mar del Plata)
🏢 AgileEngine
📍 Mar del Plata