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, Saa S 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
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