AI Data Engineer
Power Digital
| Company | Power Digital |
| Category | Engineering |
| Location | Remote - Argentina; Remote - Brazil; Remote - Colombia; Remote - Mexico |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 16 Apr 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Who We Are:
We are a tech-enabled growth firm–at the intersection of marketing, consulting & data intelligence–igniting revenue and brand recognition for leading and emerging companies around the world. As a people-first firm, we value diversity in backgrounds and experiences. We strongly believe our people and culture are key to our success. Our vision is to be recognized as the most valued and respected private growth marketing firm in the world–with a scalable brand, culture and services. Our mission is to power the relentless pursuit of growth and redefine what’s possible through a team of growth-obsessed experts who demand innovation and results - driven by integrity, autonomy, and grit.
As a full-service growth marketing firm, we offer best-in-class services including: SEO, Content Marketing, Paid Media, Social Media Marketing, Programmatic + CTV, Public Relations, Influencer Marketing, Email + SMS, Conversion Rate Optimization, Retail Marketing, and Creative. Here at Power Digital, we are hyper-focused on helping brands drive revenue growth and brand recognition, ultimately driving irrefutable value for our clients.
At the heart of Power Digital is our proprietary technology, nova, which analyzes businesses through first-party data, simplifying investment planning for marketing and diligence in M&A––putting marketers in a strategic seat at the table––and providing value in unparalleled ways.
Managing billions in media, our dynamic team––of consultative marketers, creatives, analysts and technologists––challenge traditional ways of planning and measurement through meticulous testing and data science across each milestone of the customer journey. ***Proficiency in spoken and written English at an advanced level is required for this role.
A day in the life:
You operate at the intersection of data engineering and applied AI, building end-to-end solutions that power Power Digital’s internal AI platform. Your work goes beyond traditional data pipelines — you take ownership from raw data ingestion through to AI-ready outputs and features. You collaborate closely with data science and product teams, ensuring that data systems directly translate into functional AI capabilities used across the organization.
Responsibilities:
Build and own end-to-end data pipelines in Snowflake — from raw ingestion through transformation to serving layers for AI products
Partner with ML engineers and data scientists to build and maintain AI-specific data infrastructure
Consolidate fragmented data sources across the organization into reliable, automated pipelines
Design scalable data models and marts that serve both analytics and ML feature engineering
Support rapid iteration on new data products and features in a fast-moving environment
Collaborate cross-functionally with analytics, data science, and product teams to translate requirements into data solutions
Proactively monitor and resolve data quality issues, optimizing for cost and performance
Employ AI technologies to enhance and optimize business processes
Utilize and leverage Power Digital's Nova ecosystem as it relates to your department
Use AI coding tools as part of your daily development workflow to accelerate pipeline development and data quality work
Role Requirements:
Strong proficiency in Python and SQL
Experience building end-to-end data solutions, from ingestion to production use
Experience with Snowflake or a similar cloud data warehouse
Working knowledge of AWS (e.g., S3, Lambda, EventBridge)
Understanding of data modeling and structuring data for downstream applications
Familiarity with Git and basic CI/CD practices
Active use of AI tools in development workflows (e.g., Claude Code, Cursor, Copilot)
Comfortable shipping fast and iterating from live user feedback
Hands-on exposure to AI workflows (e.g., embeddings, vector databases, RAG systems)
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