AgileEngine is an Inc. **** 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.
AgileEngine is an Inc. **** 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
: Versátil schedule with remote and office options.
We have an exciting and rewarding opportunity for you to take your data engineering career to the next level.
As a Data Engineer III at JPMorgan Chase within the Commercial & Investment Bank, you are part of an agile team that works to enhance, design, and deliver the software components of the firm's state‐of‐the‐art technology products in a secure, stable, and scalable way.
#J-*****-Ljbffr

📌 Senior Data Engineer (Aws) — Remote & High-Impact (Quilmes)
🏢 coderio | Software
📍 Quilmes