Senior Node.Js & Ts Backend Engineer - Remote

Bluelight; La Plata; Remote; ARS 92,241,000 - 138,361,000; Full time

Job summary

Bluelight is seeking a Senior Data Engineer to own end-to-end data pipelines from ad accounts and CRMs through Adverity into a BigQuery warehouse. You will design scalable transformations with dbt/Dataform, ensure data quality, and enable fast Looker Studio dashboards for education-focused partners.

The role is remote with an async team, offering competitive compensation based on experience and location. You will directly shape the agency's reporting backbone for education and nonprofit clients.

Qualifications

• 5+ years of hands-on data engineering experience in marketing or agency environments.
• Strong SQL with BigQuery experience in transformation and modeling.
• Expertise with dbt or Dataform pipelines.
• Python proficiency for API connections and automation.
• Experience with CRM data flows (Salesforce, HubSpot, Slate).
• Understanding of marketing metrics (ROAS, CPA, CAC).
• Git and multi-client data environments with data segregation.
• Ability to translate complex data workflows for non-technical audiences.

Responsibilities

• Own data ingestion & pipeline architecture—connect APIs from paid media platforms into Adverity and build scalable pipelines to the dashboard.
• Own CRM integration—maintain reliable CRM data connections (Slate, Salesforce, HubSpot).
• Own the data warehouse—design and optimize Google BigQuery schemas and storage.
• Own transformation & mapping—build modular SQL pipelines with dbt or Dataform.
• Own CI/CD & data segregation—manage GitHub Actions and test automation for multi-client environments.
• Enable the reporting layer—create Looker Studio dashboards and Google Sheets reports.
• Drive data quality—monitor pipelines, validate data, and flag issues.

Skills

Data engineering

SQL

dbt/Dataform

Python

API integration

CRM data flows

Analytics storytelling

Git workflows

Marketing metrics

Data quality

Tools

Adverity

Google BigQuery

Looker Studio

dbt/Dataform

GitHub Actions

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