Principal Data Engineer

About Prodege

Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.

As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today!

We are looking for a Principal Data Engineer to shape the future of data s is a high-impact role for someone who wants to own more than pipelines. You will help build the next-generation data platform that powers analytics, experimentation, machine learning, business intelligence, and revenue-driving decision-making across Prodege’s products and business domains. In this role, you will own the data stack end to end — from platform architecture and data modeling, to pipeline delivery, governance, observability, and the business outcomes those systems enable.

• The architecture and evolution of the next-generation data platform / lakehouse
• High-scale batch, ELT, and near-real-time data pipelines that power BI, experimentation, ML, and product systems
• Trusted data foundations across Snowflake, dbt, Iceberg, Trino, streaming, event-driven systems, and similar modern data technologies
• Platform patterns for Medallion architecture, data contracts, schema evolution, governance, and observability
• Data foundations that support machine learning, feature pipelines, experimentation, and decisioning
• Hands‑on technical leadership across the Data Engineering organization through direct contribution, design reviews, and mentoring
• The evolution of Data Engineering toward a more AI-first way of working

• Lead the design, build, and evolution of the next-generation data platform across Snowflake, dbt, Iceberg, Trino, Kafka, and related technologies
• Personally drive critical implementations in the data platform, modernizing legacy pipelines and proving out new approaches before scaling them across the team
• Build and optimize high-scale batch, ELT, and near-real-time pipelines for BI, product, experimentation, and ML use cases
• Establish durable platform patterns around Medallion architecture, data contracts, schema management, lineage, observability, and governance
• Design and evolve scalable data models and data marts that support business reporting, self‑service analytics, and ML workloads
• Make key decisions on tooling, orchestration, storage patterns, performance, reliability, and cost efficiency
• Partner closely with ML, BI, Product, Engineering, Analytics, and business stakeholders to turn business needs into scalable technical designs
• Build data foundations that support model training, feature pipelines, experimentation, and AI-driven applications
• Drive an AI-first mindset by using AI to accelerate development, debugging, design exploration, testing, and documentation
• Mentor data engineers and raise the bar on technical quality, maintainability, and engineering discipline

• 6+ years of hands‑on experience in Data Engineering, ideally in AdTech, Mar Tech, Growth, consumer internet, or other high‑scale / multi-product environments
• Strong hands‑on expertise in SQL, Python, Snowflake, and dbt
• Proven experience designing and building modern data platforms at scale
• Strong experience with: batch and near-real-time data pipelines streaming / event-driven architectures modern data modeling and ELT patterns
• Medallion architecture, data contracts, and schema evolution
• Proven experience modernizing complex, interconnected data systems with strong ownership
• Experience building production-grade data systems that support BI, experimentation, product analytics, and ML use cases
• Strong judgment across performance, scalability, reliability, and cost tradeoffs
• Experience partnering cross-functionally with Data…