Senior Database Engineer - MarketOnce

At MarketOnce , we empower businesses with the insights and strategies they need to excel in today's dynamic market. With a strong foundation in market research, we offer innovative solutions in research, software, consulting, advertising, and marketing to corporate, private equity firms, and other organizations seeking to achieve their goals.

Our team is distinguished by their client-centric approach—treating each client's business with the dedication and care as if it were their own. This commitment enables us to deliver personalized service and achieve the highest standards of success and innovation in everything we do. Together, our family of companies, including MarketOnce , ROI Rocket, and eAccountable, work towards delivering unparalleled solutions. Headquartered in Denver, Colorado, our global team collaborates from locations across the US and Europe.

We value curiosity, creativity, collaboration, and expertise, continuously striving to push boundaries and exceed our clients' expectations. Join us to be part of a culture that drives meaningful results.

About the Opportunity:

As a Sr. Database Engineer, you’ll join a close-knit team building the future of a platform designed to power immersive digital experiences for our customers and partners. In this role, you will leverage deep technical expertise to design, optimize, and operationalize large-scale data solutions spanning distributed compute, datalake, Relational and Vector databases that ensure high performance, scalability, and reliability. You'll work across the full modern data stack — from Lakehouse foundations to real-time inference — enabling advanced analytics, semantic search, and AI-driven capabilities at scale.

What You'll Do:

• Analyze and optimize production data solutions to identify and resolve issues related to performance, locking, and scalability
• Write and optimize complex SQL across the full stack — Spark SQL for distributed transformations, PostgreSQL for transactional and analytical workloads, and Delta Lake for versioned, ACID-compliant table management
• Design and build large-scale Spark and Azure Data Factory pipelines for batch and streaming ingestion, transformation, and feature engineering — leveraging both PySpark and Spark SQL for distributed processing at large scale
• Design and develop data lake architectures including Medallion Architecture to support advanced analytics and large-scale data ingestion
• Build and maintain production-grade data pipelines for efficient data movement and transformation across systems. Managing Delta table lifecycles, schema evolution, Z-ordering, time travel, and Change Data Feed to support reliable, performant analytics and OLTP and ML workloads
• Design and operate hybrid storage patterns combining PostgreSQL for transactional workloads — with optimized schemas, indexes, CTEs, window functions, and partitioning — alongside Delta Lake Lakehouse layer