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.

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.

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.

perks and benefits

- professional growth : accelerate your professional journey with mentorship, techtalks, and personalized growth roadmaps.
- competitive compensation : we match your ever-growing skills, talent, and contributions with competitive usd-based compensation and budgets for education, fitness, and team activities.
- a selection of exciting projects : join projects with modern solutions development and top-tier clients that include fortune 500 enterprises and leading product brands.
- flextime : tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office - whatever makes you the happiest and most productive.

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📌 Senior data platform engineer id92207 (México)
🏢 Agileengine
📍 México