Staff Data Platform Engineer - Ingestion & Integrations

Agileengine, Llc.; Rosario; Ibrido; ARS 185.448.000 - 278.173.000; Tempo pieno

Vantaggi offerti da questo lavoro

Professional growth

Competitive compensation (USD-based)

Flextime: remote and office options

Descrizione del lavoro

AgileEngine in Rosario, Argentina, is seeking a Senior Data Engineer to operate and enhance a Snowflake-based enterprise data platform in a regulated healthcare environment. You will lead complex incidents, design robust data pipelines, and collaborate with Cloud/DevOps to ensure data quality and reliability.

The role requires strong SQL and Python skills, experience with dbt and ingestion tools, and a focus on observability. Flexible remote options and LatAm coverage support are offered.

Competenze

• 5+ years of professional data engineering experience.
• Snowflake-based data platform design, performance and troubleshooting.
• Advanced SQL skills with dbt for transformation and testing.
• Experience with data ingestion tools such as Fivetran or HVR.
• Hands-on AWS data services, especially S3.
• Experience with Argo Workflows on Kubernetes.
• Python or similar language for data tooling.
• Strong data modeling, schema evolution, and data quality practices.
• Observability, logging, alerting, and incident-management discipline.
• Ability to lead incidents, perform root-cause analysis, and drive preventive actions.

Mansioni

• Provide senior ownership for Data Platform operations during LatAm hours.
• Operate Snowflake production and non-production environments; manage sizing and monitoring.
• Administer data access with least-privilege controls and audit readiness.
• Oversee data ingestion across Fivetran/HVR and custom pipelines.
• Design, build, and maintain pipelines and dbt models across RAW, CURATED, CONSUMPTION.
• Support AWS S3 lake operations and coordinate downstream Snowflake workloads.
• Coordinate with Cloud/DevOps for Argo/Kubernetes hosted data workloads.
• Define data quality and observability standards and automations.
• Lead major data incidents, perform RCA, and implement preventive actions.
• Mentor engineers and ensure effective handoffs across the team.
• Participate in Data Platform on-call rotation.

Conoscenze

Data engineering experience

Snowflake platform

Advanced SQL

dbt

Fivetran/HVR

AWS data services (S3)

Argo Workflows/Kubernetes

Python

Data modeling

Observability/Incident mgmt

Leadership & mentoring

English communication

On-call readiness

Strumenti

Fivetran

HVR

dbt

Argo

Kubernetes

Tableau Cloud

Descrizione del lavoro

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.