Senior Snowflake Data Platform Engineer - Remote

Chainlink; Buenos Aires; Hybrid; ARS 185,448,000 - 278,173,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine is seeking a Senior Data Engineer to operate and improve a Snowflake-based data platform in a regulated healthcare environment. You will own day-to-day operations and tackle complex troubleshooting.

Strong SQL, dbt, Fivetran/HVR, AWS data services, Argo on Kubernetes, Python; lead incidents, mentor engineers, and collaborate with Cloud/DevOps, Analytics, Security, and stakeholders. This role requires US Pacific Time hours and on-call rotation.

Qualifications

• 5+ years of professional experience in Data Engineering or Data Platform Engineering.
• Snowflake expertise including data-layer design and production troubleshooting.
• Advanced SQL and dbt for transformation, testing, documentation, lineage, and controlled deployment.
• Experience with Fivetran or HVR and ingestion pipelines.
• Hands-on AWS data services usage, especially S3.
• Experience with Argo Workflows on Kubernetes; workflow orchestration.
• Python or similar language for data engineering and automation.
• Strong data modeling, pipeline dependencies, and data quality.
• Observability, logging, alerting, and incident-management in production.
• Lead incidents, root-cause analysis, and preventive actions.
• Technical decision-making and cross-team improvements.
• Mentor engineers and collaborate with Cloud/DevOps, Analytics, Security, etc.
• Strong English communication with client stakeholders.
• Availability to work 9:00 AM–6:00 PM PT and on-call rotation.

Responsibilities

• Provide senior technical ownership for the Data Platform during LatAm coverage window.
• Operate Snowflake production and non-production environments; optimize performance and lifecycle.
• Administer data access with least-privilege controls and audit readiness.
• Manage data ingestion via Fivetran/HVR and custom pipelines.
• Design and maintain pipelines and dbt models across RAW, CURATED, CONSUMPTION.
• Support AWS S3 data-lake operations and data workflows.
• Coordinate with Cloud/DevOps for Argo/Kubernetes workloads.
• Define data quality and observability standards and checks.
• Expand monitoring and lineage using tools like SynQ, dbt, and Splunk.
• Lead major data incidents and post-incident reviews.
• Mentor and enable handoffs across the distributed service team.
• Participate in Data Platform on-call rotation.
• Create runbooks and knowledge-transfer materials.

Skills

Snowflake

Advanced SQL

dbt

Fivetran/HVR

AWS (S3)

Argo Workflows

Kubernetes

Python

Data modeling

Observability/Incident mgmt

Incident leadership

Mentoring

English communication

Time-zone coordination (PT)

Tools

Argo Workflows

Kubernetes

Terraform

CI/CD

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.

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.

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.

PERKS AND BENEFITS

- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.

- Competitive compensation: USD‑based pay with education, fitness, and team activity budgets.

- Exciting projects: Modern solutions with Fortune 500 and top product companies.

- Flextime: Flexible schedule with remote and office options.