Overview As a Sr. Data Engineer on this team, you will own the design and delivery of complex data pipelines, integrations, and data models that serve as the foundation of our analytics and reporting capabilities. Working closely with the Sr. Data Engineering Manager and the Enterprise Data Architect, you will translate top-down architectural decisions into production-grade implementations — and serve as a technical authority and mentor for the broader data engineering team. You bring strong judgment about when to apply analytical vs. operational data patterns, and you build to a standard rather than just to a deadline. Key Responsibilities Design, build, and maintain scalable batch and real-time data ingestion pipelines from complex source systems including ERP data, SaaS applications, and internal databases Implement and maintain data solutions in Snowflake and other appropriate platforms that align to enterprise data models defined by the architecture team, supporting BI and analytics analyst consumption with a consistent, reliable single version of truth Apply sound judgment in selecting appropriate data storage and processing patterns — OLAP vs. OLTP — based on latency, consistency, cost, and use case requirements Ensure all data engineering solutions align to target state architecture; actively participate in architecture discussions and surface implementation considerations to the Enterprise Data Architect Contribute to integration design and implementation using Boomi, Talend, custom-built integrations, or other appropriate tooling; help rationalize and standardize integration patterns across the team Partner with the Enterprise Data Architect to implement and enforce data lineage, transformation transparency, and architectural standards Drive data quality practices including pipeline monitoring, anomaly detection, and root cause resolution Author and maintain comprehensive documentation of business rules, transformation logic, and data mappings embedded in production pipelines Provide technical mentorship to Data Engineers; contribute to coding and documentation standards and participate in code reviews Translate complex business requirements into detailed technical designs independently, and validate those designs against architectural principles Identify and champion process improvements including pipeline automation, standardization, and optimization of data delivery Collaborate with BI and analytics analysts, IT teams, and business stakeholders to ensure data is modeled, documented, and accessible for their use cases Provide accurate effort estimates; participate in intake and work tracking to ensure delivery predictability Required Qualifications Advanced proficiency in SQL across both OLAP platforms (Snowflake) and relational/OLTP databases (MSSQL, Postgres, or equivalent) Clear understanding of OLAP vs. OLTP architectural patterns — including tradeoffs in latency, cost, consistency, and appropriate use cases — with demonstrated experience applying this judgment in production environments Ability to write pipeline, transformation, and automation code using Java, Python, or a comparable scripting language Demonstrated experience designing and implementing ELT/ETL pipelines using Boomi, Talend, or equivalent enterprise integration tools Strong understanding of data integration patterns across heterogeneous source systems Experience with data quality frameworks and the ability to apply monitoring and automation to detect and surface issues Ability to independently translate business requirements into detailed technical designs Strong documentation skills with the ability to produce artifacts consumable by both technical and non-technical stakeholders Experience mentoring or technically leading junior engineers Understanding of data governance principles, data lifecycle management, and data privacy and security constraints Preferred Qualifications Familiarity with XML/XPath and structured data formats including JSON for pipeline and integration development Experience with enterprise data modeling for analytics (dimensional, Data Vault, or similar) Working knowledge of Shell/Bash scripting for server configuration tasks such as tunnel setup and environment management Experience with S3 or similar cloud object storage as a staging or landing layer Exposure to data catalog or data lineage tooling (Alation, Collibra, or equivalent) Experience with workflow orchestration tools (Airflow, dbt, or equivalent) Experience participating in or supporting a formal data governance program Exposure to CDC (Change Data Capture) patterns for near-real-time data integration