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: Versátil schedule with remote and office options.

Requirements

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. Availability to work from 9:00 AM to 6:00 PM Pacific Time and participate in an agreed on-call rotation.

- Location: LATAM
- Work Model: 100% Remote
- Project: Identity Security / Cybersecurity Platform
- Seniority: Senior
- Engagement: Full-time

143L - Senior Data Engineer (Python/Go/Data Ingestion/Cloud) · Remote · LATAM

- Location: LATAM
- Work Model: 100% Remote
- Project: Identity Security / Cybersecurity Platform
- Seniority: Senior
- English Level: B2 / C1
- Engagement: Full-time

Get to Know Darwoft

At Darwoft, we build custom software solutions and partner with international companies to create high-impact digital products.

We are a Latin American technology company with a people-first culture, strong professional standards, and a long-term partnership mindset. We work with distributed teams, complex technical challenges, and clients whose technology has a direct impact on their businesses and users.

About the Project

We are partnering with an innovative cybersecurity company building a next-generation Identity Security and Identity Observability platform.

The product helps enterprise security teams understand how human users, service accounts, workloads, applications, and AI-driven identities access systems across cloud, SaaS, network,



endpoint, and on-premise environments.

At the core of the platform is a highly data-intensive architecture that collects and analyzes large volumes of events, logs, network telemetry, identity activity, and security signals. This information is processed to identify unusual access patterns, security risks, identity blind spots, infrastructure misconfigurations, and potential threats.

The platform integrates with complex enterprise ecosystems including identity providers, cloud platforms, SASE solutions, SIEMs, endpoint security tools, network infrastructure, and security services.

About the Role

We're looking for a Senior Data Engineer focused on Data Ingestion, Integrations, and Collectors to become a key technical bridge between enterprise customers and the engineering organization.

This is not a traditional backend or internal data engineering position.

You'll work directly with customers to understand their infrastructure, data sources, security architecture, network topology, APIs, and workflows, then design and implement scalable mechanisms to ingest that information into the platform.

You'll combine data engineering, software engineering, solution architecture, cloud infrastructure, and technical consulting.

A major part of your mission will be building and evolving connectors and ingestion pipelines capable of integrating data from complex enterprise environments while maintaining reliability, scalability, security, and fast time-to-production.

What You’ll Be Doing

- Design, develop, and maintain production-grade data collectors, connectors, and ingestion services.
- Integrate enterprise data sources including identity providers, cloud platforms, SASE solutions, network infrastructure, endpoints, applications, security platforms, and SIEM systems.
- Work directly with enterprise customers to understand their environments, data flows, APIs, security requirements, and integration constraints.
- Participate in technical onboarding processes, from initial discovery and architecture design through production deployment.
- Design scalable ingestion architectures for processing security events, logs, identity activity, network telemetry, and other high-volume data sources.
- Build integrations using REST APIs, cloud-native services, event-driven architectures, and modern software engineering practices.
- Develop backend services primarily using Python and/or Go.
- Work with SQL and NoSQL databases to store, transform, query, and analyze high-volume data.
- Build and operate containerized services using Docker and Kubernetes.
- Deploy and integrate solutions across AWS, Azure, and GCP environments.
- Troubleshoot complex customer deployment and integration issues across application, infrastructure, networking, API, and data layers.
- Optimize ingestion performance, reliability, scalability, and operational efficiency.
- Collaborate with Solution Architects, Sales Engineering, Customer Success, Product, and Engineering teams.
- Act as a trusted technical advisor around customer data architecture, collection strategies, security integrations, and implementation best practices.
- Identify recurring customer requirements and transform them into reusable connectors, platform capabilities, or improvements to the core product.
- Contribute technical insights from real-world implementations to the product roadmap.
- Support production adoption and continuously improve time-to-value for enterprise customers.
- Participate in occasional customer-facing technical sessions and, when necessary, onsite engagements.

What You Bring

- 10+ years of professional Software Engineering, Data Engineering, Platform Engineering, or related experience.
- Strong software development experience with:
- Python
- Go

- Strong experience designing and consuming REST APIs.
- Hands-on experience building data ingestion pipelines, connector frameworks, integration platforms, or similar systems.
- Experience integrating complex enterprise systems and third-party platforms.
- Solid understanding of both SQL and NoSQL databases.
- Production experience with at least one major cloud platform:

- AWS
- Azure
- GCP

- Experience working with Docker and Kubernetes.
- Strong understanding of Git-based development workflows and CI/CD practices.
- Experience designing reliable, scalable, and production-ready distributed systems.
- Strong debugging skills across APIs, infrastructure, networking, application services, and data pipelines.
- Experience working directly with customers, stakeholders, or technical partners.
- Ability to translate complex customer requirements into pragmatic technical solutions.
- Strong communication skills and the ability to operate effectively in customer-facing technical conversations.
- High degree of autonomy and ownership when solving ambiguous technical problems.

Highly Relevant Experience

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