Senior Data & Business Intelligence Engineer

Accountabilities: Design, build, operate, and continuously improve enterprise Data Lake and Data Lakehouse solutions. Develop scalable ETL and ELT pipelines capable of efficiently processing terabytes of data across batch and streaming workloads. Build and support real-time analytics platforms and distributed data services using technologies such as Oracle Database, Debezium, Kafka, Kafka Connect, Apache Flink, Apache Iceberg, Nessie, StarRocks, Spark, Kyuubi, and Power BI. Implement Change Data Capture, event-driven processing, schema evolution, data versioning, data cataloging, metadata management, and data lineage capabilities. Establish data quality, reconciliation, governance, monitoring, observability, anomaly detection, and alerting frameworks. Troubleshoot production data services, perform backfills and large-scale data transformations, and optimize platform and query performance. Support Linux-based production environments, including administration, systemd-managed services, automation, monitoring, performance tuning, and incident resolution. Develop advanced SQL, data models, dimensional structures, semantic layers, and analytical datasets that support enterprise reporting and self-service analytics. Help ensure data platforms and analytics solutions appropriately handle sensitive information, including personally identifiable information, customer data, confidential business information, and other regulated data. Partner with stakeholders to translate business and analytical needs into scalable technical solutions and trusted insights. Provide technical leadership on complex initiatives, participate in architecture and code reviews, mentor team members, and contribute to engineering standards and best practices. Stay current with emerging technologies and actively use AI-enabled tools, copilots, automation platforms, and other modern solutions to improve productivity, problem-solving, and engineering efficiency while maintaining appropriate security and compliance practices. Requirements Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or a related field, or an equivalent combination of education, professional experience, and demonstrated technical expertise. 5+ years of experience in data engineering, analytics engineering, business intelligence engineering, or a closely related discipline. Proven experience designing and implementing enterprise Data Lakes, Data Lakehouses, or analytical data platforms. Strong experience developing enterprise-scale ETL/ELT solutions and reliable, scalable data pipelines. Hands-on experience with modern data technologies such as Oracle Database, Debezium, Kafka, Kafka Connect, Apache Flink, Apache Iceberg, Nessie, StarRocks, Spark, Kyuubi, and Power BI is highly desirable. Experience with CDC, event-driven architectures, real-time data processing, schema evolution, data versioning, metadata management, data lineage, and data cataloging. Experience supporting large-scale data ingestion, transformation, reconciliation, backfill processes, distributed analytics platforms, and production troubleshooting. Familiarity with observability and SRE practices and tools such as Prometheus, VictoriaMetrics, and Grafana. Strong experience working with production Linux environments such as Oracle Linux, RHEL, CentOS, or equivalent platforms. Advanced SQL development, data modeling, query optimization, dimensional modeling, semantic-layer design, and analytical data structure skills. Experience implementing data quality, governance, monitoring, reconciliation, observability, anomaly detection, and alerting frameworks. Experience supporting enterprise reporting, self-service analytics, curated datasets, semantic models, and high-performance analytical query engines. Strong analytical, problem-solving, troubleshooting, and performance optimization abilities. Demonstrated ability to provide technical leadership, mentor team members, conduct code and design reviews, and establish engineering best practices. Excellent communication and collaboration skills, with the ability to work effectively with technical and business stakeholders. A curious, adaptable, and AI-forward mindset, with the ability to adopt emerging tools and technologies thoughtfully. Candidates must be legally eligible to work in the United States or Canada and able to travel internationally as required. A valid passport and any required travel authorization are necessary. Preference may be given to candidates able to work within the Eastern Time Zone. Benefits Salary range of $80,000–$110,000 . Fully remote work within the United States or Canada. Approximately 1–2 business trips per year to Vermont, customer locations, or other destinations as needed. Three weeks of vacation plus five personal days. Comprehensive medical, dental, and vision coverage beginning on the first day of employment. Employee stock ownership opportunities. RRSP/401(k) matching programs. Lifestyle rewards and additional employee perks. Opportunities to work with modern data, analytics, and AI-enabled technologies. Professional development and opportunities to contribute to evolving engineering standards and practices. Inclusive workplace with reasonable accommodations available to qualified applicants.