Data Engineer

The Data Warehouse Engineer designs, builds, and optimizes scalable data pipelines that connect solution-area source systems to InvoiceCloud s enterprise data warehouse. This role focuses on enabling reliable analytics, data science, and reporting by developing automated workflows, improving performance, and maintaining strong data quality standards. You will work closely with technology teams and business stakeholders to translate operational and analytical requirements into durable data warehouse solutions that support enterprise decision-making. Success Profile At InvoiceCloud, success is anchored in our core competencies. These competencies guide how every employee delivers impact across their role Results Driven Delivers reliable, scalable data pipelines that support analytics, reporting, and data science initiatives. Translates business and operational requirements into effective warehouse designs and data models. Diagnoses and resolves issues in high-volume data processing systems to minimize downtime and protect data integrity. Ensures warehouse architecture supports performance, accuracy, and enterprise analytics needs. Takes Ownership Designs, develops, and maintains automated, real-time data pipelines from multiple source systems into the data lake and warehouse. Maintains deep understanding of source systems and downstream consumers to champion data usability and reliability. Implements auditing, logging, and data quality controls to ensure consistency and trust in data workflows. Owns issue resolution across ingestion, transformation, and delivery layers, coordinating with partners as needed. Drives Efficiency Optimizes pipeline and query performance using SQL, Python, profiling tools, and tuning techniques. Implements scalable Snowflake development workflows that reduce rework and accelerate delivery. Applies strong ETL/ELT design principles to streamline data movement and lifecycle management. Participates in architecture reviews and contributes to best practices that improve warehouse scalability and maintainability. Innovative Researches and adopts emerging technologies and modern architectural patterns to improve performance and scalability. Enhances warehouse capabilities to better support advanced analytics and data science initiatives. Experiments with new orchestration, automation, and monitoring approaches to improve reliability and observability. Contributes to evolving data governance standards and quality frameworks across the organization. Requirements Strong SQL expertise with proven ability to write, optimize, and maintain complex queries Experience designing and implementing modern, architecture-based data warehouses in enterprise environments Hands-on experience with cloud data warehouses such as Snowflake, Redshift, or BigQuery Proficiency in scripting or software engineering languages such as Python, Bash, or JavaScript Strong understanding of data modeling, ETL/ELT design, and data lifecycle management Ability to work with large-scale datasets from diverse source systems Ability to communicate technical concepts clearly to both technical and non-technical stakeholders