Senior Data Platform Engineer — Snowflake & AWS

AgileEngine, LLC.; Córdoba; Hybrid; ARS 230,940,000 - 323,316,000; 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 within a regulated healthcare environment. You will own day-to-day operations, optimize workloads, and drive incident response across ingestion, orchestration, and downstream analytics.

Responsibilities include building robust dbt models, managing AWS data services, coordinating with Cloud/DevOps, and ensuring data quality, observability, and cost efficiency.

Qualifications

• 5+ years of professional experience in Data Engineering or Data Platform Engineering.
• Hands-on Snowflake design, data-layer design, warehouse performance, access patterns, and production troubleshooting.
• Advanced SQL 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.

Responsibilities

• 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.

Skills

Advanced SQL

Python

Data modeling

Observability

Incident management

Mentoring

English communication

On-call coordination

Tools

Snowflake

dbt

Fivetran

HVR

AWS S3

Argo Workflows

Kubernetes

Terraform

CI/CD pipelines

Freshservice

Jira

Tableau Cloud

Job description

AgileEngine is seeking a Senior Data Engineer to operate and improve a Snowflake-based data platform within a regulated healthcare environment. You will own day-to-day operations, optimize workloads, and drive incident response across ingestion, orchestration, and downstream analytics.

Responsibilities include building robust dbt models, managing AWS data services, coordinating with Cloud/DevOps, and ensuring data quality, observability, and cost efficiency.