Senior Data Platform Engineer - Snowflake (Remote)

Medallia

Quilmes

Remote

ARS 185,448,000 - 278,173,000

Full time

43 hours ago
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Benefits offered by this job

Flexible schedule
Remote and office options
Professional growth

Job summary

AgileEngine is seeking a Senior Data Engineer to operate and enhance a Snowflake-based enterprise data platform in a regulated healthcare environment. You will own day-to-day operations, optimize workloads, and lead data ingestion, modeling, and observability initiatives.

Key focus areas include Snowflake, dbt, AWS data services, and Argo/Kubernetes-based orchestration, with rigorous data quality and incident management. Strong leadership and English communication are required.

Qualifications

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

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.
  • Help 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 extraction patterns toward 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 mid-level engineers, review technical work, and ensure effective handoffs across the distributed service team.

Skills

SQL
Python
English communication
Data modeling
Observability
Mentoring
Incident management

Tools

Snowflake
dbt
Fivetran
HVR
AWS data services
Argo Workflows
Kubernetes

Job description

AgileEngine is seeking a Senior Data Engineer to operate and enhance a Snowflake-based enterprise data platform in a regulated healthcare environment. You will own day-to-day operations, optimize workloads, and lead data ingestion, modeling, and observability initiatives.

Key focus areas include Snowflake, dbt, AWS data services, and Argo/Kubernetes-based orchestration, with rigorous data quality and incident management. Strong leadership and English communication are required.

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