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Senior Data Engineer, Business Intelligence
Harris Computer. Design, build, and support enterprise Data Lake solutions from the ground up .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and building enterprise Data Lakes and Lakehouses, with strong capabilities in developing scalable ETL/ELT solutions and managing large-scale data environments. Proficient in ensuring data quality, governance, and compliance with handling sensitive data while providing technical leadership and mentoring within data engineering teams.
Highest-signal resume keywords
Data Lake DesignETL/ELT Solutions DevelopmentLinux Environment SupportAdvanced SQL DevelopmentData Governance and Quality
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Data EngineeringAnalytics EngineeringBusiness Intelligence EngineeringETL DevelopmentData Pipeline DevelopmentSQL DevelopmentData ModelingChange Data CaptureAnomaly DetectionPerformance Tuning
Soft Skills
Technical LeadershipMentoringCollaborationProblem SolvingCommunication
Tools & Technologies
Oracle DatabaseDebeziumKafkaApache FlinkApache IcebergPower BIPrometheusGrafanaVictoriaMetricsStarRocks
Industry Keywords
Data GovernanceData QualityMetadata ManagementData LineageReal-Time Data ProcessingSelf-Service AnalyticsBusiness IntelligenceObservabilitySite Reliability EngineeringRegulated Data Compliance
Tech Stack
Tools & technologiesApacheETLGrafanaKafkaLinuxOraclePrometheusSparkSQL
About the role
Key responsibilities & impact- Design, build, and support enterprise Data Lake solutions from the ground up
- Develop scalable ETL solutions and data pipelines
- Move and process terabytes of data efficiently
- Implement data quality, data governance, metadata, and lineage processes
- Develop anomaly detection, monitoring, and alerting capabilities
- Support modern Data Lakehouse and real-time analytics platforms
- Support large-scale data ingestion, transformation, reconciliation, and backfill processes
- Troubleshoot and optimize production data services and distributed analytics platforms
- Support Linux environments and operational services for data and analytics platforms
- Support enterprise reporting, self-service analytics, and business intelligence solutions
- Ensure platforms handle sensitive and regulated data according to organizational requirements
- Provide technical leadership, mentor team members, conduct code and design reviews, and develop engineering standards
Requirements
What you’ll need- 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 related discipline
- Proven experience designing and building enterprise Data Lakes, Lakehouses, or analytical data platforms
- Strong experience developing enterprise ETL/ELT solutions and scalable data pipelines
- Experience with Oracle Database, Debezium, Kafka, Kafka Connect, Apache Flink, Apache Iceberg, Nessie, StarRocks, Spark, Kyuubi, and Power BI
- Experience with batch and streaming data workloads
- Experience with Change Data Capture (CDC), event-driven architectures, real-time data processing, data cataloging, schema evolution, data versioning, and enterprise-scale ETL/ELT solutions
- Experience supporting large-scale data ingestion, transformation, reconciliation, backfill processes, and distributed analytics platforms
- Familiarity with observability, monitoring, and Site Reliability Engineering (SRE) practices using Prometheus, VictoriaMetrics, and Grafana
- Strong experience supporting production Linux environments, including system administration, systemd-managed services, performance tuning, automation, monitoring, troubleshooting, and operational support
- Advanced SQL development, data modeling, and performance tuning skills
- Experience with dimensional modeling, semantic-layer design, and analytical data structures
- Experience processing and managing large-scale data environments
- Hands-on experience implementing data quality, reconciliation, monitoring, and observability frameworks
- Experience with metadata management, data lineage, governance, and data cataloging practices
- Experience implementing monitoring, alerting, anomaly detection, and operational support processes
- Experience supporting enterprise reporting, self-service analytics, and business intelligence solutions
- Ability to ensure compliance with requirements for handling PII, customer data, confidential business information, and other regulated data
- Ability to provide technical leadership, mentor team members, conduct code and design reviews, and contribute to engineering standards and best practices
- Current, valid passport and legal eligibility to travel internationally, including required travel visas or visa exemption for Canada, the United States, and the Caribbean
- Preference for candidates who can work in EST timezone
Benefits
Comp & perks- 3 weeks’ vacation and 5 personal days
- Comprehensive Medical, Dental, and Vision benefits starting from your first day of employment
- Employee stock ownership and RRSP/401k matching programs
- Lifestyle rewards
- Remote work