Sr. Data Engineer

Kobie Marketing•Richmond, VA

12d•Remote

About The Position

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We’re always looking for talented individuals who are ready to join a collaborative, growth-focused culture. As a partner to some of the world’s most recognized brands, we are leaders in loyalty, helping brands build lasting emotional connections with their consumers. Kobie embraces a flexible work environment, offering teammates the freedom to work remotely. We understand the importance of work-life balance and support our team with Flexible Time Off to recharge when needed, Nine Company-Wide Holidays, and A diverse suite of benefits prioritizing your growth, development, and personal well-being. Kobie is a values-led organization where we believe that everyone is a leader, regardless of their position or role. At Kobie, we turn our client’s loyalty data into actionable intelligence that drives enterprise value. Our Data Engineering team builds and maintains the operational data foundation that powers real-time dashboards, client-facing reporting, and emerging AI-driven products, serving a growing portfolio of enterprise loyalty program clients across some of the most recognized brands in the world. As a Senior Data Engineer, you will be a key technical contributor and operational owner within our data engineering function. You will bring deep Snowflake expertise and strong engineering instincts to own production data pipelines, lead client implementations, and help us evolve our data architecture to support event-driven and AI-powered workflows, all within a multi-hundred terabyte Snowflake environment where the data problems are as complex as the brands behind them.

Requirements

6+ years of Data Engineering experience designing and operating production grade data pipelines.
3+ years of hands-on Snowflake experience as a primary data warehousing solution, with deep fluency across data sharing, data clean rooms, marketplace, and Snowpark.
Strong proficiency in SQL, Python, and JavaScript for data transformation, pipeline development, and automation scripting.
Demonstrated CI/CD experience using GitHub and GitHub Actions
Experience with data replication tools (Kafka, GoldenGate, HVR, Qlik Replicate or similar)
Deep understanding of Kimball dimensional modeling: star schemas, slowly changing dimensions, snapshot and transaction fact tables.
Experience integrating a wide range of data sources, including APIs, messaging systems, and streaming platforms.
Solid grounding in OLTP, Data Vault, and data warehouse architecture patterns, with the ability to assess source systems and translate business requirements into dimensional models.
Experience designing event-driven architectures and understanding how they shape data pipeline design.
Familiarity with domain-driven design concepts and how application architecture changes flow downstream into the warehouse.
Cloud experience with Azure and/or AWS.
Comfort working independently across concurrent projects in an Agile environment, with strong communication to non-technical data stakeholders.

Nice To Haves

Prior experience in a terabyte-scale, multi-client data warehouse environment, you've worked at this kind of scale before and know what it demands.
Experience with data replication tool Qlik Replicate, preferred
Familiarity with Apache NiFi or comparable data flow orchestration tools, preferred
Exposure to AI workflow integration within a data warehousing context, or experience building pipelines that serve downstream machine learning use cases.

Responsibilities

Serve as the operational backbone of Kobie's data platform, ensuring the ETL/ELT pipelines, dimensional models, and Snowflake environments that power client reporting and dashboards run reliably, at scale, every day.
Translate client loyalty program requirements into production-ready data warehouse structures — from source system analysis and dimensional modeling through to the KALC (Kobie Alchemy Loyalty Cloud) platform tables and extracts that downstream reporting and client services teams depend on.
Diagnosing and resolve data pipeline failures quickly enough that clients and internal stakeholders rarely notice they happened by bringing the debugging fluency and Snowflake depth to contain impact and prevent recurrence.
Build a data architecture that can absorb change by redesigning Kobie's data mart to support an incoming event-driven, domain-driven application layer without breaking the operational foundation already in production.
Deliver the data infrastructure that makes AI-powered loyalty products possible. Not by building the models, but by building the reliable, well-governed platform that Kobie's innovation team needs to produce them.
Leave every pipeline more trustworthy than you found it, through automated testing, audit logging, CI/CD discipline, and documentation that makes the platform easier for the next engineer to own.