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 USIf 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 ROLEWe are looking for a Data Engineer to build data pipelines and tooling for cost attribution, optimization, and financial modeling.WHAT YOU WILL DO- Develop and implement tooling and datasets that drive telemetry-driven cost attribution and performance-informed financial modeling, enabling product, engineering, analyst, and finance stakeholders to make faster, data-driven decisions and trust the data.
- Build and maintain data pipelines and tooling that provide cost transparency, surface optimization opportunities, and support committed use discount modeling and management.MUST HAVES- 4+ years of experience in Data Engineering roles.
- Hands-on experience with SQL, Python, Spark, and Scala.
- Hands-on experience with workflow orchestration tools such as dbt, Airflow, and Dagster.
- Hands-on experience with AWS (Glue, Aurora, Athena), GCP, and Snowflake.
- Experience architecting and enhancing the long-term maintainability of end-to-end ELT/ETL data pipelines, including data modeling and schema maturity.
- Exposure to CI/CD development processes, Infrastructure as Code (Terraform), and REST API programming.
- Strong attention to detail, analytical skill, and comprehensive data auditing and end-to-end validation skills.
- Ability to explain technical concepts to non-technical audiences.NICE TO HAVES- Experience with FinOps teams or cost optimization job duties.
- FinOps Practitioner or FinOps Engineer certification.
- Experience with Datadog API endpoints.
- Experience with Go.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.Requirements+4 years of experience in Data Engineering roles.
Hands-on experience with SQL, Python, Spark, and Scala.
Hands-on experience with workflow orchestration tools such as dbt, Airflow, and Dagster.
Hands-on experience with AWS (Glue, Aurora, Athena), GCP, and Snowflake.
Experience architecting and enhancing the long-term maintainability of end-to-end ELT/ETL data pipelines, including data modeling and schema maturity.
Exposure to CI/CD development processes, Infrastructure as Code (Terraform), and REST API programming.
Strong attention to detail, analytical skill, and comprehensive data auditing and end-to-end validation skills.
Ability to explain technical concepts to non-technical audiences.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.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.Data Engineer (Marketing-oriented)



| Remote for Marketing Agency for EducationOur client is a fast-growing performance marketing agency specializing in mission-driven organizations across higher education and nonprofit sectors.
Since launching in ****, the agency has built a strong reputation for combining strategic thinking, creative execution, and data-driven marketing to help universities and organizations achieve measurable growth.Company Overview: Our client is a fast-growing performance marketing agency specializing in mission-driven organizations across higher education and nonprofit sectors.
Since launching in ****, the agency has built a strong reputation for combining strategic thinking, creative execution, and data-driven marketing to help universities and organizations achieve measurable growth.Your Role: The Senior Data Engineer sits at the center of the agency's Data and Analytics function, connecting every paid media platform and CRM the agency touches into a single, reliable source of truth.
You'll own the full path data takes: from a client's ad accounts and CRM, through Adverity, into a BigQuery warehouse, through modular dbt/Dataform transformations, and out to the Looker Studio dashboards and automated Google Sheets reports the team and its partners rely on daily.
Reporting to the Data and Analytics Manager, you're joining at a pivotal moment — the agency is scaling its roster of education and nonprofit partners, and this role is instrumental in evolving the automated reporting suite that makes that growth possible without sacrificing data quality or client trust.You'll:Own data ingestion & pipeline architecture — connect and maintain API pipelines from paid media platforms (Meta, Google Ads, LinkedIn, TikTok, programmatic) into Adverity, build custom Python connectors for anything not natively supported, and architect scalable pipelines from source system through to dashboardOwn CRM integration — build and maintain reliable CRM data connections (Slate, Salesforce, HubSpot) so lead and enrollment data flows cleanly into the warehouseOwn the data warehouse — route, optimize, and store raw and processed data in Google BigQuery; design efficient schemas for complex, multi-source marketing data (granularity, normalization, slowly changing dimensions); manage partitioning, clustering, and storage strategy to control query cost and performanceOwn transformation & mapping — build SQL schemas that map, blend, and organize multi-channel data accurately for each client, in modular, version-controlled, documented dbt or Dataform pipelines, with standardized naming conventions and metric definitions across platforms and clientsOwn CI/CD & data segregation — maintain CI/CD pipelines (GitHub Actions, automated testing) for robust, version-controlled releases, and enforce strict data segregation across multi-client environmentsEnable the reporting layer — create clean, performant data views built specifically for fast Looker Studio dashboards and automated Google Sheets reports, and partner with the Data and Analytics Manager and client teams to translate reporting requirements into warehouse modelsDrive data quality — monitor pipeline health, resolve API breaks, minimize latency, implement validation frameworks and automated testing, troubleshoot discrepancies to root cause across source/warehouse/BI layers, and proactively flag data quality risks to leadershipYou Bring:5+ years of hands-on data engineering experience, ideally in a marketing or agency environmentStrong experience configuring datastreams, transformations, and destinations in Adverity or a comparable ETL platform (Fivetran, Supermetrics, Funnel)Intermediate to advanced SQL, with proven BigQuery experience in transformation, partitioning, and modelingExpertise in dbt or Dataform, managing modular, version-controlled, documented SQL transformation pipelinesPython proficiency for custom API connections and pipeline automationExperience with CRM data flows and integrations (Slate, Salesforce, and/or HubSpot)A deep understanding of marketing metrics (ROAS, CPA, CAC) and paid platform schemas, with a proven track record of structuring data to optimize Looker Studio performanceProficiency with Git and collaborative development workflows, and proven ability to manage multi-client data environments with strict data segregationAn analytical, solution-driven mindset with a growth orientation, and strong communication skills that turn complex data workflows into clear narratives for non-technical audiences — education marketing experience (traditional or online) is especially valuedBonus Points:Experience integrating AI-driven insights or machine learning models into marketing data pipelines to sharpen predictive analytics and data utilityFamiliarity using AI or LLM tools to optimize performance forecasting, automated audience segmentation, or marketing workflowsExperience connecting, managing, and maintaining APIs for generative AI platforms within a marketing data architectureExperience using AI/ML-driven anomaly detection to monitor pipelines and proactively flag data quality issuesWhat's Offered:Remote role with the flexibility that comes with a distributed, async-friendly teamCompetitive compensation based on experience and locationA pivotal, high-visibility seat on a scaling Data & Analytics team, with real ownership over the agency's reporting infrastructureThe chance to build the data backbone for an agency whose partners are education and nonprofit organizations working to build a better worldA culture built around finding a better way, playing as a team of A-players, and treating results as the engine rather than the goalDirect impact: the pipelines and models you build directly shape how partners see (and trust) their own performance dataInterview Process:1.
Application Review (resume + a few questions)2.
Screening Call with Atomic HR3.
Hiring Team Interview (walkthrough of a pipeline or data model you've built)4.
Technical Assessment (a real-world data engineering case study)5.
Final Interview with company leadershipLocation: LATAMWork Model: 100% RemoteProject: Identity Security / Cybersecurity PlatformSeniority: SeniorEngagement: Full-time143L - Senior Data Engineer (Python/Go/Data Ingestion/Cloud) · Remote · LATAMLocation: LATAMWork Model: 100% RemoteProject: Identity Security / Cybersecurity PlatformSeniority: SeniorEnglish Level: B2 / C1Engagement: Full-timeGet to Know DarwoftAt 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 ProjectWe 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.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 RoleWe'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 DoingDesign, 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 Bring10+ years of professional Software Engineering, Data Engineering, Platform Engineering, or related experience.Strong software development experience with:PythonGoStrong 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:AWSAzureGCPExperience 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 ExperienceExperience with any of the following will be especially valuable:Identity and Access Management (IAM)Identity Providers (IdPs)Identity SecurityCybersecurity platformsSIEM systemsSecurity telemetryNetwork securityEndpoint securitySASE / Zero Trust environmentsCloud securityLarge-scale event processingStreaming architecturesIntegration ExperiencePrevious experience integrating APIs or data from platforms such as the following is highly valuable:AWSMicrosoft AzureGoogle CloudMicrosoft Entra ID / Active DirectoryOktaGoogle WorkspaceDuoCrowdStrikeZscalerPalo AltoMicrosoft DefenderSIEM and security analytics platformsDirect experience with every platform is not required.
What matters is a strong track record of learning complex APIs and transforming heterogeneous enterprise data sources into reliable integrations.Nice to HaveExperience with large-scale data processing or streaming platforms.Experience designing reusable connector SDKs or integration frameworks.Understanding of identity-related security concepts such as authentication, authorization, credentials, service accounts, privileged access, and non-human identities.Experience with security events, audit logs, network telemetry, or cloud activity data.Familiarity with event-driven and distributed system architectures.Experience deploying AI/ML-enabled applications.Exposure to LLMs, AI agents, or AI-powered security applications.Solution Architecture or Forward Deployed Engineering experience.Previous experience in cybersecurity startups or high-growth SaaS environments.What Success Looks LikeSuccess in this role will be measured by your ability to:Deliver successful enterprise integrations and deployments.Reduce customer time-to-production.Build reliable and scalable ingestion solutions.Improve customer adoption and technical satisfaction.Resolve complex integration challenges efficiently.Turn customer-specific requirements into reusable platform capabilities.Contribute improvements that strengthen the scalability and flexibility of the core product.What Darwoft OffersContractor agreement with payment in USD100% remote workArgentina's public holidaysEnglish classesReferral programAccess to learning platformsExplore this and other opportunities at:
#J-*****-Ljbffr

📌 Remote Senior Marketing Data Engineer | Bigquery & Pipelines (Quilmes)
🏢 BforeAI
📍 Quilmes