Remote .Net Analytics Platform Engineer - Bi & Sql Pro

Campari Group; Ciudad de Mendoza; Ibrido; ARS 139.086.000 - 200.903.000; Tempo pieno

Vantaggi offerti da questo lavoro

Professional growth

USD-based pay

Exciting projects

Flextime

Descrizione del lavoro

AgileEngine in LATAM 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, performance optimization, and data ingestion across multiple pipelines.

The role requires advanced SQL and Python, dbt modeling, Fivetran/HVR, AWS S3, and Argo Workflows on Kubernetes, with strong data quality and observability.

Competenze

• 5+ years of professional experience in Data Engineering.
• Snowflake experience including data modeling and production issues.
• Advanced SQL skills with dbt for transformation, testing and lineage.
• Experience with Fivetran or HVR and custom ingestion pipelines.
• AWS data services, especially S3 and event/file-based ingestion.
• Argo Workflows on Kubernetes experience.
• Python or equivalent for data engineering and automation.
• Strong data modeling, dependencies, schema evolution, and data quality.
• Observability, logging, alerting and incident management.

Mansioni

• Provide senior technical ownership for the Data Platform service tower during the LatAm coverage window.
• Operate and improve Snowflake production and non-production environments, including warehouse configuration and sizing, performance monitoring, and support for production changes.
• Administer data access with least-privilege controls and audit-ready practices.
• Operate and improve data ingestion across Fivetran, HVR, and custom pipelines.
• Design, build, and maintain pipelines and dbt models across RAW, CURATED, and CONSUMPTION layers with testing, lineage, and CI/CD.
• Support AWS S3 data-lake operations, including lifecycle controls and access patterns.
• Coordinate with Cloud/DevOps on Argo Workflows and Kubernetes-hosted workloads.
• Define and improve data quality and observability standards (freshness, row-count, nulls, schema drift).
• Expand end-to-end monitoring and lineage using SYNQ, dbt, Snowflake audit data, Splunk.
• Lead or support major data incidents and post-incident reviews across ingestion, orchestration, Snowflake, and Tableau dependencies.
• Support Tableau Cloud operations where needed.
• Identify and deliver standardization, automation, reliability, performance, and cost improvements.

Conoscenze

Snowflake

dbt

Fivetran/HVR

AWS S3

Argo Workflows

Kubernetes

Python

Data Modeling

Data Quality

Observability

Strumenti

Tableau Cloud

Jira

Freshservice

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.