Senior Data Platform Engineer

RIVO Holdings•San Diego, CA

5d•Onsite

About The Position

RIVO is seeking an experienced Senior Data Platform Engineer to help architect and build the modern data platform that will power our next phase of growth. We're looking for a builder. Someone who can assess where we are today, define where we need to be tomorrow, and help lead the journey. As our first in-house Senior Data Platform Engineer, you'll design the foundation for analytics, machine learning, and near real-time data processing while helping shape the architecture, technologies, and engineering standards that support our long-term vision. Success in this role requires understanding the differences between platforms built for reporting and business intelligence versus those designed to support data science and machine learning workloads. As both a strategic architect and hands-on engineer, you'll play a key role in transforming a legacy database and data structure into a scalable, modern platform built for the future. If you're energized by ownership, attracted to complex challenges, and motivated by the opportunity to build something lasting, we'd love to hear from you!

Requirements

8+ years in Data Warehousing or Data Platform Engineering, including enterprise-scale data warehouses, lakehouses, analytics platforms, dimensional modeling (Star Schema, Snowflake Schema, Fact Tables and Dimension Tables)
Experience supporting both analytics and data science workloads, including low-latency and near real-time data environments and ML pipelines.
Experience designing and implementing modern Data Warehouse or Data Lake, along with data governance and data classification.
Experience designing and implementing solutions using Microsoft Fabric, Databricks, Snowflake, Azure Data Lake Storage, or similar modern cloud data technologies.
Experience building ETL/ELT pipelines, CDC and incremental processing strategies, enterprise-scale SQL and Python solutions, query optimization, performance tuning, partitioning, indexing, data reconciliation, and recovery processes.

Responsibilities

Design and implement a modern enterprise data warehouse, lakehouse, or hybrid data platform architecture.
Develop the target-state architecture for analytics, reporting, and data science.
Establish the foundational architecture needed to support future scalability, low-latency performance, and real-time data availability.
Modernize legacy ETL-driven warehouse processes.
Define ingestion, transformation, storage, and consumption layers across the platform.
Design and implement CDC-based ingestion and incremental data processing strategies.
Build low-latency ETL/ELT pipelines supporting near real-time data availability.
Design scalable semantic layers and consumption models across the platform.
Establish data quality, testing, monitoring, and observability frameworks.
Design a scalable data warehouse to support real-time enterprise reporting and analytics.
Develop data structures that balance the needs of business intelligence, analytics, and data science.
Implement historical data retention and governance strategies.
Enable trusted, self-service data consumption across the organization.
Partner with Engineering, Product, Analytics, and Data Science teams to define data requirements and priorities.
Translate business needs into scalable data platform solutions.
Provide technical leadership through collaboration and mentorships.
Serve as a trusted advisor on data architecture, governance, and platform strategy.

Benefits

Childcare reimbursement up to $5,000 annually
Comprehensive fertility treatment coverage
FREE weekly group workouts
Regular happy hours and company-wide events
Exclusive access to season long raffle drawings in the RIVO ticket section for Padres tickets
FREE coffee, energy drinks, and snacks
Company-paid parking or MTS pass
Perfect attendance incentive
Company paid holidays and PTO
Medical, dental, and vision plans with a 70/30 cost share
401(k) plan with employer matching