Senior Data Platform Engineer ID92207

AgileEngine, LLC.; Ciudad de Mendoza; On-site; ARS 136,430,000 - 197,065,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation (USD-based)

A selection of exciting projects

Flextime

Job summary

AgileEngine is seeking a Senior Data Engineer in Mendoza to own and evolve a Snowflake-based data platform within a regulated healthcare environment. You will lead L2/L3 support, optimize warehouses, and implement robust data pipelines end-to-end.

You will collaborate with Cloud/DevOps, Data Analytics, Security, and stakeholders; drive data quality and observability, incident post-mortems, and mentor engineers while participating in on-call rotations.

Qualifications

• 5+ years of professional experience in Data Engineering or Data Platform Engineering.
• Hands-on Snowflake design, warehouses, access patterns, and production troubleshooting.
• Advanced SQL and dbt for transformation, testing, lineage, and controlled deployment.
• Experience with Fivetran or HVR and custom ingestion pipelines.
• Hands-on AWS data services, especially S3 and event/file ingestion patterns.
• Experience with Argo Workflows on Kubernetes and related scheduling/troubleshooting.
• Python for data engineering and automation.
• Strong data modeling, dependencies, schema evolution, and data quality.
• Observability, logging, alerting, and incident-management for production data platforms.
• Proven incident resolution and root-cause analysis.
• Ability to guide platform improvements and technical decisions.
• Mentoring engineers and collaborating with Cloud/DevOps, Analytics, Security, Governance, stakeholders.
• Strong written and verbal English; client-facing.
• Full availability to work 9:00 AM–6:00 PM PT and participate in on-call rotation.

Responsibilities

• Provide senior technical ownership for the Data Platform during LatAm coverage window.
• Operate and improve Snowflake production and non-production environments.
• Administer data access with least-privilege and audit-ready practices.
• Manage data ingestion via Fivetran/HVR and custom pipelines.
• Design, build and maintain pipelines and dbt models across RAW, CURATED, CONSUMPTION.
• Support AWS S3 data-lake operations with lifecycle and logging.
• Coordinate with Cloud/DevOps for Argo Workflows and Kubernetes workloads.
• Define data quality and observability standards.
• Expand end-to-end monitoring and lineage with tools like SYNQ, dbt, Snowflake audit data, Splunk.
• Lead or support major data incidents and post-incident reviews.
• Support Tableau Cloud operations when needed.
• Deliver standardization, automation, reliability, and cost improvements.
• Run incident/change/release processes with service-management workflows.
• Create runbooks, procedures, and knowledge-transfer materials.
• Mentor middle-level engineers and ensure effective handoffs.
• Participate in Data Platform on-call rotation.

Skills

Snowflake

SQL

dbt

Fivetran

HVR

Python

Data modeling

Observability

Incident management

English communication

Tools

Argo Workflows on Kubernetes

Kubernetes

Terraform

CI/CD pipelines

Freshservice

Jira

Job description

MENDOZA, Argentina | Posted on 10/01/2026

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.