Senior Data Platform Engineer ID92207

AgileEngine; Belo Horizonte; Hybrid; BRL 643,000 - 965,000; 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 data ingestion, modeling, and observability while mentoring engineers and coordinating with Cloud/DevOps for reliable, scalable pipelines across RAW, CURATED, and CONSUMPTION layers.

Join a people-first culture with opportunity to impact Fortune 500 brands and startups.

Qualifications

• 5+ years of professional data engineering experience.
• Strong Snowflake data platform experience with design and troubleshooting.
• Advanced SQL and dbt for transformations, testing and lineage.
• Experience with Fivetran/HVR and ingestion pipelines.
• AWS data services usage with S3 and ingestion patterns.
• Experience with Argo Workflows on Kubernetes or similar.
• Python or equivalent language for data tooling and automation.
• Knowledge of data modeling, lineage, and data quality.
• Experience in observability, logging, and incident management.
• Ability to mentor engineers and collaborate with cross-functional teams.

Responsibilities

• Own data platform operations during LatAm coverage with escalation handling.
• Operate Snowflake in production and non-production environments with tuning.
• Administer data access with least-privilege and audit-ready practices.
• Manage data ingestion across Fivetran/HVR and custom pipelines.
• Design and maintain pipelines and dbt models across RAW, CURATED, CONSUMPTION.
• Support S3 lake operations, lifecycle, and downstream Snowflake workloads.
• Coordinate with Cloud/DevOps for Argo/Kubernetes workloads.
• Define data quality and observability standards with measurable checks.
• Expand monitoring and lineage using SYNQ, dbt, Snowflake, Splunk.
• Lead major data incidents and perform root-cause analysis.
• Support Tableau Cloud operations when needed.
• Deliver automation and cost improvements; follow ITSM processes.
• Create runbooks, procedures, and knowledge transfer materials.
• Mentor mid-level engineers and ensure smooth handoffs across teams.
• Participate in on-call rotation for critical incidents.

Skills

Data engineering

SQL

Python

dbt

Data modeling

Observability

Incident management

Mentoring

English communication

On-call support

Tools

Snowflake

Fivetran

HVR

Argo Workflows

Kubernetes

Tableau Cloud

AWS

Splunk

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.