Remote Senior Marketing Data Engineer (Bigquery/Python)

Sophilabs, Inc.; Santa Fe Capital; Remote; ARS 181,672,000 - 272,508,000; Full time

Benefits offered by this job

Remote work

Job summary

Darwoft is seeking a Senior Data Engineer focused on data ingestion and integrations to support a cyber security platform for enterprise clients. You will design and maintain connectors, ingestion services, and scalable pipelines that handle identity, cloud, and network data.

You will work directly with customers to understand environments and constraints, implement REST APIs and modern architectures, and ensure reliable, secure data flows across AWS, Azure and GCP. Remote LATAM-based role.

Qualifications

• 5+ years of hands-on data engineering in marketing or agency environments.
• Experience configuring datastreams, transformations, and destinations in Adverity or comparable ETL platforms (Fivetran, Supermetrics, Funnel).
• Intermediate to advanced SQL with BigQuery experience in transformation, partitioning, and modeling.
• Expertise in dbt or Dataform for modular, version-controlled SQL pipelines.
• Python proficiency for custom API connections and pipeline automation.
• Experience with CRM data flows (Slate, Salesforce, HubSpot).
• Deep understanding of marketing metrics (ROAS, CPA, CAC) and platform schemas for Looker Studio performance.
• Proficiency with Git and multi-client data environments with strict data segregation.

Responsibilities

• Design, develop, and maintain production-grade data collectors, connectors, and ingestion services.
• Integrate enterprise data sources including identity providers, cloud platforms, and SIEM systems.
• Collaborate with customers to understand environments, data flows, security requirements, and integration constraints.
• Participate in onboarding, architecture design, and production deployment.
• Design scalable ingestion architectures for processing high-volume data sources like events, logs, and telemetry.
• Build integrations using REST APIs, cloud-native services, and event-driven architectures.
• Develop backend services with Python and/or Go; work with SQL and NoSQL databases.
• Operate containerized services using Docker and Kubernetes; deploy across AWS, Azure, and GCP.
• Troubleshoot deployments, optimize ingestion performance, and ensure data security and reliability.
• Collaborate with solution architects, sales engineering, customer success, and product teams.

Skills

SQL

BigQuery

Python

dbt/Dataform

ETL pipelines

CRM data

Marketing metrics

Git

Tools

Adverity

Fivetran

Supermetrics

Funnel

Docker

Kubernetes

AWS

Azure

GCP

Job description

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 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 .

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