Senior Data Engineer: Ingestion & Analytics Remote

Power Digital Marketing; Municipio de Rincón de los Sauces; Remote; ARS 182,310,000 - 273,465,000; Full time

Benefits offered by this job

Remote work

Contractor payments in USD

Career growth

Job summary

Darwoft is seeking a Senior Data Engineer focused on data ingestion, connectors, and cloud integration to partner with enterprise customers. You will design scalable ingestion pipelines using Python/Go, build robust data connectors, and collaborate with architects and product teams to deliver secure, high‑volume data solutions in a remote LATAM setting.

The role emphasizes working directly with customers, owning ingestion architectures, and delivering production-grade data pipelines across AWS,

Qualifications

• Strong proficiency in Python and Bash, with SQL as a core skill.
• Experience building data ingestion pipelines and connectors.
• Hands-on cloud experience across AWS, Azure, or GCP.
• Familiarity with Docker and Kubernetes for containerized services.
• Ability to work directly with customers to gather requirements and design scalable data solutions.

Responsibilities

• Design, develop, and maintain production-grade data collectors, connectors, and ingestion services.
• Integrate enterprise data sources including identity providers, cloud platforms, SASE, network infrastructure, endpoints, applications, security platforms, and SIEM systems.
• Work directly with enterprise customers to understand environments and requirements.
• Develop scalable ingestion architectures for processing security events, logs, identity activity, and high-volume data.
• Build integrations using REST APIs, cloud-native services, event-driven architectures, and modern software practices.
• Develop backend services using Python and/or Go.
• Operate Docker and Kubernetes-based services.
• Deploy across AWS, Azure, and GCP.
• Collaborate with Solution Architects, Sales Engineering, Customer Success, Product, and Engineering.
• Identify requirements and convert into reusable connectors and platform improvements.

Skills

Python

Go

SQL

REST APIs

Docker

Kubernetes

CI/CD

Data ingestion

Tools

Terraform

dbt

GitHub

BigQuery

Job description

Coderio designs and delivers scalable digital solutions for global companies. We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end. We work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.

More information:

This is a high-impact technical role. We are looking for a motivated and adaptive DataOps Engineer, Technical Referent to join our fast-paced environment. You will operate at the intersection of data engineering, cloud infrastructure, and DevOps, where a high tolerance for ambiguity and a passion for constant learning are essential. Your primary mission involves interacting with customers to understand their needs, extract requirements, and both design and propose scalable solutions. You will be responsible for tackling the challenge of working within a team to develop solutions, as well as executing hands-on technical work to ensure robust data operations.

What To Expect In This Role (Responsibilities)

Automation & Integration: Develop Python components, Terraform modules, and pipelines to integrate and automate various tools and processes.

API & System Orchestration: Promote the use of APIs from distinct systems to extract and update data, trigger and monitor processes, and help tie infrastructures together.

Cloud Reliability & Operations: Deploy, maintain, and oversee cloud infrastructure to ensure it runs with the performance and reliability our customers expect.

Data Modeling & Documentation: Help create Data Models, technical documents, and best practices for our users.

DataOps Best Practices & Innovation: Develop policies, processes, and best practices regarding DevOps and DataOps. You will also help identify opportunities, generate innovative solutions, and improve existing product features.

Requirements

Development & Scripting: Strong proficiency in Python and bash, and fluency in SQL as a second language.

Data Ecosystems & Pipelines: Deep familiarity with databases, data warehouses, and data lakes, as well as being adept at data pipelines and process improvement.

Cloud & Tooling Mastery: Strong knowledge of AWS environments, including EC2, Lambda, IAM, SQS, RDS, Kinesis, Glue, and EKS. Must also be familiar with modern development tools like Terraform, GitHub, Docker, and dbt.

Mindset & Work Style: Ability to thrive in an environment with constant and quick iterations, consistently seeking out creative solutions to challenging problems. Must have strong attention to detail.

Autonomy & Collaboration: Ability to work collaboratively while also being capable of owning a project with little guidance. Must be comfortable working in a diverse environment and non-hierarchical organizations.

Customer-Facing Skills: Ability to interact directly with customers to understand needs, extract requirements, and propose technical solutions.

Nice to Have

AWS associate or professional-level certifications, such as Solutions Architect, Developer, or DevOps Engineer.

High-impact, strategic role driving modern data infrastructure and automation.

Collaborative international environment with senior technical leadership.

High autonomy to design, propose, and implement cutting-edge DataOps solutions.

Long-term engagement with competitive compensation and growth opportunities.

Why Join Coderio?

At Coderio, we value talent and technical excellence. We are passionate about modern engineering, high autonomy, and building solutions that make a real difference. We offer an inclusive and challenging environment where innovation is encouraged and technical leadership is valued. If you are eager to design and deploy next-generation data solutions that elevate engineering teams, apply now.

BigQuery

• 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

Experience with any of the following will be especially valuable:

• Identity and Access Management (IAM )
• Identity Providers (IdPs )
• Identity Security
• Cybersecurity platforms
• SIEM systems
• Security telemetry
• Network security
• Endpoint security
• SASE / Zero Trust environments
• Cloud security
• Large-scale event processing
• Streaming architectures

Integration Experience

Previous experience integrating APIs or data from platforms such as the following is highly valuable:

• AWS
• Microsoft Azure
• Google Cloud
• Microsoft Entra ID / Active Directory
• Okta
• Google Workspace
• Duo
• CrowdStrike
• Zscaler
• Palo Alto
• Microsoft Defender
• SIEM and security analytics platforms

Direct 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 Have

• Experience 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 Like

Success 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 Offers

• Contractor agreement with payment in USD
• 100% remote work
• Argentina's public holidays
• English classes
• Referral program
• Access to learning platforms

Explore this and other opportunities at:

Data Engineer (Marketing-oriented) | Remote for Marketing Agency for Education

Our client is a fast‑growing performance marketing agency specializing in mission‑driven organizations across higher education and nonprofit sectors. Since launching in 2020, 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 2020, 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 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 dashboard
• Own CRM integration — build and maintain reliable CRM data connections (Slate, Salesforce, HubSpot) so lead and enrollment data flows cleanly into the warehouse
• Own 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 performance
• Own 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 clients
• Own 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 environments
• Enable 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 models
• Drive 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 leadership

You Bring:

• 5+ years of hands‑on data engineering experience, ideally in a marketing or agency environment
• Strong 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 modeling
• Expertise in dbt or Dataform, managing modular, version‑controlled, documented SQL transformation pipelines
• Python proficiency for custom API connections and pipeline automation
• Experience 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 performance
• Proficiency with Git and collaborative development workflows, and proven ability to manage multi‑client data environments with strict data segregation
• An 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 valued

Bonus Points:

• Experience integrating AI‑driven insights or machine learning models into marketing data pipelines to sharpen predictive analytics and data utility
• Familiarity using AI or LLM tools to optimize performance forecasting, automated audience segmentation, or marketing workflows
• Experience connecting, managing, and maintaining APIs for generative AI platforms within a marketing data architecture
• Experience using AI/ML‑driven anomaly detection to monitor pipelines and proactively flag data quality issues

What’s Offered:

• Remote role with the flexibility that comes with a distributed, async‑friendly team
• Competitive compensation based on experience and location
• A pivotal, high‑visibility seat on a scaling Data & Analytics team, with real ownership over the agency's reporting infrastructure
• The chance to build the data backbone for an agency whose partners are education and nonprofit organizations working to build a better world
• A culture built around finding a better way, playing as a team of A‑players, and treating results as the engine rather than the goal
• Direct impact: the pipelines and models you build directly shape how partners see (and trust) their own performance data

Interview Process:

• Application Review (resume + a few questions)
• Screening Call with Atomic HR
• Hiring Team Interview (walkthrough of a pipeline or data model you've built)
• Technical Assessment (a real‑world data engineering case study)
• Final Interview with company leadership