Senior Ai Orchestration Deployment Engineer (Remote)

Camunda

Santa Fe Capital

Remote

ARS 90,873,000 - 181,747,000

Full time

3 days ago

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Benefits offered by this job

Remote work with async-friendly team

Competitive compensation

Job summary

Camunda is seeking a Senior Data Engineer focused on marketing analytics to consolidate paid media and CRM data into a single warehouse. You will own end-to-end pipelines, from ingestion to dashboards, ensuring accuracy and scalable reporting for education-focused clients.

You’ll work on modular, version-controlled SQL transformations, build custom Python connectors, and collaborate with cross-functional teams to translate data into clear business insights.

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.
Strong SQL, with BigQuery transformation and modeling experience.
Expertise in dbt or Dataform for modular pipelines with version control.
Python proficiency for custom API connections and automation.
CRM data flows (Slate, Salesforce, HubSpot) and warehouse integration.
Understanding marketing metrics (ROAS, CPA, CAC) and Looker Studio performance.
Proficient Git skills and multi-client data environment management.
Analytical mindset with clear communication for non-technical stakeholders.

Responsibilities

Own data ingestion and pipeline architecture connecting paid media and CRM to Adverity and the warehouse.
Build reliable CRM connections (Salesforce/HubSpot) feeding the central data store.
Design and optimize the Google BigQuery warehouse and schemas for multi-source marketing data.
Develop SQL schemas in modular dbt/Dataform pipelines with clear naming conventions.
Maintain CI/CD pipelines and enforce data segregation across clients.
Create performant data views for Looker Studio dashboards and automated reports.

Skills

Data pipeline design

SQL & BigQuery

dbt/Dataform

Python for API integration

ETL/ELT platforms (Adverity)

CRM data flows (Salesforce, HubSpot)

Looker Studio reporting

Git & CI/CD

Multi-client data environments

Data quality & testing

Tools

Adverity

Fivetran

Supermetrics

Funnel

Looker Studio

dbt

Dataform

BigQuery

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:

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: