Data Engineer

Black Canyon Consulting (BCC) is searching for a Data Engineer to support the design, development, and maintenance of data infrastructure that enables artificial intelligence, machine learning, and analytical workloads. The Data Engineer will help ensure that data is reliable, accessible, scalable, and operationally ready throughout the full lifecycle from ingestion through deployment.

The Data Engineer will design, implement, maintain, and optimize data pipelines, APIs, data transformation workflows, and supporting infrastructure. This position will work with databases, data lakes, data warehouses, feature stores, and other data platforms to ensure information can be efficiently ingested, transformed, accessed, and used by analytical and AI-enabled systems.

The Data Engineer will also develop and maintain ETL/ELT processes, feature engineering workflows, and service layers that expose data or model endpoints to downstream systems and applications.

• Experience designing, developing, and maintaining data pipelines
• Experience building and optimizing ETL and/or ELT workflows
• Experience working with relational and/or non-relational databases
• Experience integrating databases, data lakes, data warehouses, or similar data platforms
• Experience developing data transformation workflows
• Experience supporting data used for analytical, AI, or machine learning workloads
• Experience developing or integrating APIs and service layers
• Strong understanding of data reliability, accessibility, quality, and operational readiness
• Experience monitoring, troubleshooting, and optimizing data pipelines
• Understanding of data modeling and data architecture principles
• Strong programming and problem-solving skills
• Ability to work collaboratively with software engineers, data scientists, analysts, and other technical stakeholders

• Senior: 8+ years of relevant experience
• Mid-Level: 5+ years of relevant experience
• Junior: 3+ years of relevant experience

• Experience supporting machine learning or artificial intelligence environments
• Experience developing feature engineering workflows or working with feature stores
• Experience designing data infrastructure for high-volume or distributed systems
• Experience with cloud-based data platforms and infrastructure
• Experience developing APIs that expose data, analytical results, or model endpoints
• Experience with automated data pipeline monitoring and alerting
• Experience optimizing data pipelines for performance, reliability, and scalability
• Experience working with modern data lakehouse or warehouse architectures
• Experience implementing data validation, testing, and quality controls

• →Design, implement, and maintain scalable data pipelines supporting analytical and AI/ML workloads
• →Build, monitor, troubleshoot, and optimize ETL and ELT data pipelines
• →Develop workflows for ingesting, transforming, processing, and delivering data
• →Configure and integrate databases, data lakes, data warehouses, feature stores, and other data platforms
• →Develop and maintain data transformation and feature engineering processes
• →Ensure data reliability, accessibility, quality, and operational readiness
• →Develop APIs and service layers to expose data or model endpoints to downstream applications and systems
• →Collaborate with data scientists, software engineers, analysts, and other technical teams to support data requirements
• →Monitor pipeline performance and resolve data processing or integration issues
• →Implement processes to validate data accuracy, completeness, and consistency
• →Support deployment and operation of data infrastructure throughout the system lifecycle
• →Identify opportunities to improve pipeline scalability, performance, maintainability, and efficiency
• →Document data pipelines, integrations, transformations, and technical processes