Latam Senior Data Engineer - Ai-Driven Bi Pipelines

Lever, Inc.; La Pampa; Remote; ARS 136,430,000 - 197,065,000; Full time

Benefits offered by this job

Remote role

Ownership and impact on reporting

Competitive compensation

Job summary

Darwoft is seeking a Senior Data Engineer for a marketing analytics platform, focused on building scalable data pipelines from paid media and CRM sources into BigQuery and Looker Studio dashboards. You will own ingestion, transformation, and data quality across multi-client environments in a fully remote LATAM setup.

The role emphasizes SQL, dbt/Dataform, Python, and CI/CD, with strong collaboration with the Data & Analytics team and client stakeholders to deliver reliable, scalable reporting

Qualifications

• 5+ years of hands-on data engineering experience in marketing or agency environments.
• Experience with Adverity or similar ETL platforms (Fivetran, Supermetrics, Funnel).
• SQL with BigQuery experience for transformation and modeling.
• Expertise with dbt or Dataform for modular pipelines.
• Python for API connections and automation.
• CRM data flows with Slate, Salesforce, or HubSpot.
• Understanding of marketing metrics (ROAS, CPA, CAC) and Looker Studio performance.
• Git and collaborative workflows; multi-client data environments with data segregation.
• Strong communication and education marketing experience valued.

Responsibilities

• Own data ingestion and pipeline architecture across paid media and CRM sources.
• Maintain reliable CRM connections (Slate, Salesforce, HubSpot).
• Manage the data warehouse in BigQuery with scalable schemas.
• Build modular dbt/Dataform transformations with clear naming.
• Maintain CI/CD pipelines for robust releases.
• Create data views for Looker Studio dashboards and Google Sheets reports.
• Monitor data quality and resolve API breaks; ensure data governance.

Skills

5+ years data engineering

Adverity ETL

SQL (BigQuery)

dbt / Dataform

Python

CRM data flows

Marketing metrics (ROAS)

Git & CI/CD

Education marketing exposure

Tools

Looker Studio

GitHub Actions

Adverity / ETL tools

Job description

BigQuery

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 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 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

Location: LATAM
Work Model: 100% Remote
Project: Identity Security / Cybersecurity Platform
Seniority: Senior
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 Opportunity

We're partnering with an innovative software company building a modern transaction platform for organizations managing complex M&A processes. The platform brings together document workflows, collaboration, approvals, diligence, transaction management, and AI‑powered capabilities within a single SaaS product.

What makes this opportunity particularly different is the way the engineering team builds software. The product has been developed using an AI‑native engineering approach, with tools such as Claude Code, OpenAI Codex, and other AI coding agents deeply integrated into the development workflow.

We're looking for a highly experienced Senior / Staff Software Engineer who can combine strong software engineering fundamentals with this new way of building software. This is not a traditional AI/ML Engineer role.

You won't be training machine learning models or working primarily on Data Science. Instead, you'll be engineering production software, navigating a large existing codebase, making architectural decisions, improving reliability, and using AI coding agents to dramatically increase development velocity.

The ideal person is a builder first: highly technical, pragmatic, product‑oriented, low‑ego, and comfortable taking ownership of complex systems.

What You'll Be Doing

• Navigate, understand, and evolve a large existing production codebase.
• Design and implement new product capabilities across a complex SaaS platform.
• Make pragmatic architectural and system design decisions as the product continues to scale.
• Identify technical debt, architectural risks, reliability issues, and opportunities for improvement.
• Use Claude Code, Codex, Cursor, Copilot, or similar AI coding agents extensively throughout the software development lifecycle.
• Leverage AI agents to explore codebases, design implementations, generate and refactor code, debug issues, write tests, and accelerate delivery.
• Build and evolve backend services, APIs, integrations, data models, and application workflows.
• Contribute across the application stack when needed.
• Strengthen automated testing, maintainability, observability, reliability, and production readiness.
• Improve development workflows, tooling, automation, and engineering practices.
• Troubleshoot complex issues across application, data, and infrastructure layers.
• Balance development speed with software quality and long‑term maintainability.
• Work closely with product leadership to translate business problems into effective technical solutions.
• Help a small engineering team achieve significantly greater development leverage through AI‑assisted engineering.

What You Bring

• Strong professional experience building and operating production software systems.
• Excellent software engineering fundamentals, including architecture, system design, debugging, testing, and maintainability.
• Experience working with large or complex existing codebases.
• Strong backend or full‑stack engineering experience using modern programming languages and frameworks.
• Experience building modern web applications and SaaS products.
• Strong understanding of APIs, application architecture, integrations, data modeling, and distributed systems.
• Experience with relational databases and production data environments.
• Strong understanding of automated testing and modern software development practices.
• Familiarity with cloud environments, CI/CD pipelines, deployments, and production operations.
• Ability to reason through technical trade‑offs and make pragmatic architectural decisions.
• Strong ownership and ability to work independently in an evolving product environment.
• Product mindset: you understand not only how to build something, but also why it should be built.

AI‑Native Engineering Experience

Hands‑on experience using AI development tools is especially important for this position.

We're particularly interested in engineers who actively use tools such as:

• Claude Code
• OpenAI Codex
• Cursor
• GitHub Copilot
• Windsurf
• Other AI coding agents or agentic development tools

More importantly, we're looking for someone who uses AI beyond code completion.

You should be comfortable using AI to:

• Understand unfamiliar codebases.
• Investigate architecture and dependencies.
• Design implementations.
• Generate and refactor production code.
• Debug complex issues.
• Create and improve automated tests.
• Review code and identify potential issues.
• Automate repetitive engineering tasks.
• Accelerate delivery while maintaining engineering quality.

We're looking for someone who sees AI as a core engineering tool, while still bringing the technical judgment required to make strong software and architectural decisions.

Nice to Have

• Experience working in early‑stage or high‑growth product companies.
• Previous experience as a Staff Engineer, Principal Engineer, Tech Lead, Founding Engineer, or similar high‑ownership role.
• Experience building AI‑powered SaaS products.
• Experience integrating LLMs or AI APIs into production applications.
• Experience with document‑heavy or workflow‑intensive platforms.
• Experience designing authorization systems, permissions, RBAC, and auditability.
• Experience with LegalTech, FinTech, transaction platforms, Private Equity, or other complex B2B SaaS products.
• Experience improving engineering productivity through developer tooling and automation.

What Success Looks Like

Success in this role goes beyond writing more code.

• Help the team ship significantly faster while simultaneously strengthening the architecture, reliability, maintainability, and technical maturity of the platform.
• The goal is to combine strong engineering judgment with AI‑native development practices to dramatically increase what a small engineering team can build.

What Darwoft Offers

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