Costa Rica, Perm MKS

As a Data Engineer, you bring a strong technical curiosity and a focus on building scalable, reliable data systems. With 3–5 years of experience, you design and maintain data pipelines, models, and infrastructure supporting digital marketing and web analytics data across paid and owned channels. You work closely with cross-functional teams to translate measurement requirements into well-structured, automated data solutions, while continuously improving data quality, performance, and architectural standards.

 

You will:

Data Engineering & Infrastructure

· Design, build, and maintain scalable data infrastructure to support the ingestion, transformation, storage, and retrieval of digital marketing and web analytics data.

· Develop, automate, and optimize ETL pipelines using Rivery and Power Automate, and or other ETL tools.

· Integrate data from web analytics platforms, media platforms, APIs, and third-party data sources.

· Implement robust data models aligned with downstream analytics and reporting requirements while ensuring performance and sustainability.

· Ensure data reliability through validation, monitoring, documentation, and governance best practices.

· Prepare datasets that support efficient consumption by BI tools, analytics workflows, and advanced modeling.

Data Frameworks & Architecture

· Build and maintain data engineering frameworks and reference architectures that improve scalability, reusability, and performance.

· Develop prototypes and proof-of-concept pipelines to test new data sources, tools, and architectural patterns.

Collaboration & Enablement

· Partner with analytics, media, engineering, and strategy teams to translate business and measurement requirements into technical data solutions.

· Collaborate with partner agencies and internal stakeholders to deliver end-to-end data solutions.

· Contribute to agile planning, estimation, and execution for data engineering initiatives.

 

You have:

· B.S. degree in a quantitative or technical field. Including but not limited to: statistics, mathematics, business, finance, social sciences, computer science, or information management.

· Hands-on experience working with web analytics data, preferably Adobe Analytics.

· Strong understanding of digital media channels (e.g., Social, SEM, SEO, OLV) from a data and tracking perspective.

· Familiarity with marketing attribution models (e.g., MTA, MMM) from a data engineering and modeling standpoint.

· Experience designing and maintaining data models for analytics and reporting use cases.

· Working knowledge of APIs, data ingestion patterns, and data integration best practices.

· Curiosity, ownership mindset, and a strong desire to continuously learn and improve data systems.

· Experience with cloud-based data platforms such as AWS, Snowflake, or similar enterprise data environments.

· Familiarity with GenAI tools as part of data engineering, automation, or analytics workflows.

What We Offer:

• Maternity and parental leave extra days
• Competitive benefits packages
• Vacation, compassionate leave, sick days, and flex days
• Access to online services for families and new parents
• Diversity and Inclusion Board with 12 affinity groups
• Internal learning and development programs
• Enterprise-wide employee discounts
• And more…

Critical Mass is an equal opportunity employer. 

Critical Mass uses artificial intelligence in our recruitment process to enhance job postings, filter keywords during the review of prospective candidates, and, in some cases, transcribe interviews with our recruiters. Human review remains central to the process, and all hiring decisions are ultimately made by our team.

The Critical Mass Talent Acquisition team will only communicate from email addresses that use the URLs criticalmass.com, omc.com and us.greenhouse-mail.io. We will not use apps such as Facebook Messenger, WhatsApp, or Google Hangouts for communicating with you. We will never ask you to send us money, technology, or anything else to work for our company. If you believe you are the victim of a scam, please review your local government consumer protections guidance and reach out to them directly.

If U.S. based: https://www.consumer.ftc.gov/articles/job-scams#avoid
If Canada based: https://www.canada.ca/en/services/finance/consumer-affairs.html
If U.K. based: https://www.gov.uk/consumer-protection-rights
If Costa Rica based: https://www.consumo.go.cr/educacion_consumidor/consejos_practicos.aspx