Principal Data Engineer

Prodege, LLC is a cutting-edge marketing and consumer insights platform focused on innovation in technology. They are seeking a Principal Data Engineer to lead the design and implementation of their next-generation data platform, driving analytics, machine learning, and business intelligence initiatives across the organization.

Responsibilities:

• 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

Requirements:

• 6+ years of hands-on experience in Data Engineering, ideally in AdTech, MarTech, 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
• Strong experience with streaming / event-driven architectures
• Strong experience with modern data modeling and ELT patterns
• Strong experience with Medallion architecture
• Strong experience with 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 Science, BI, Product, Engineering, and business teams
• Ability to guide teams toward an AI-first way of working, while maintaining strong validation and engineering discipline
• Strong technical leadership and mentoring capability, with the ability to influence across teams without direct authority
• Comfort operating in ambiguity and still driving systems into production
• Experience with Iceberg, Trino, Kafka, Kinesis, Apache Flink, or similar modern lakehouse / streaming technologies
• Familiarity with feature stores, model-serving pipelines, and DataOps practices
• Experience supporting experimentation platforms, self-serve BI, or performance marketing use cases
• Experience in consumer rewards, surveys, monetization, or marketplace-style ecosystems
• Experience with cloud-native data stacks and modern observability tooling
• Familiarity with AI-assisted or AI-first development practices across data teams