Data Warehouse & Analytics Engineer

System Enhancement & Data Warehouse Support

• Evaluates, enhances, and maintains technology performance data warehouse solutions, reporting capabilities, and analytics platforms.
• Develops and supports data structures, processes, and applications that improve access to technology performance metrics and operational insights.
• Designs, develops, tests, and implements enhancements that align with existing system architecture and enterprise technology standards.
• Identifies opportunities to improve solution performance, scalability, maintainability, and reliability.

Data Ingestion & Source Integration

• Develops and maintains data ingestion processes that integrate information from technology platforms, operational systems, vendor applications, and other internal and external data sources.
• Supports source-to-target mappings, data integration requirements, and data movement processes.
• Develops and maintains interfaces utilizing APIs, database connectivity, and file-based integrations to ensure efficient and reliable data acquisition.
• Collaborates with business and technology stakeholders to identify new data requirements and integration opportunities.

Data Transformation & Curation

• Develops and maintains ETL/ELT processes that transform source data into trusted analytics-ready datasets.
• Applies business rules, data validations, standardization processes, and transformation logic to support reporting and analytical requirements.
• Ensures data consistency, accuracy, usability, and alignment with established business definitions and reporting standards.

Analytics Data Modeling

• Designs, develops, and maintains analytical and dimensional data models that support technology performance management, reporting, dashboards, scorecards, and KPI measurement.
• Supports reporting and analytics initiatives through the development of optimized data structures and reporting datasets.
• Collaborates with stakeholders to translate business requirements into effective analytical data solutions.

Historical Data & Snapshot Management

• Maintains historical data repositories and snapshot methodologies to support trend analysis, forecasting, benchmarking, audit requirements, and long-term performance measurement.
• Ensures historical data structures support consistent reporting and analysis across reporting periods.
• Implements processes that preserve data lineage and historical integrity.

Data Quality Controls

• Develops and maintains data quality controls, validation procedures, reconciliation processes, and monitoring solutions.
• Identifies, researches, and resolves data integrity issues, anomalies, and discrepancies.
• Partners with source system owners and stakeholders to improve data quality and ensure confidence in reporting outputs.
• Supports data governance, documentation, and compliance requirements where applicable.

Business Support & Operational Excellence

• Provides technical support to production data warehouse and analytics environments by addressing complex issues, anticipating maintenance requirements, and ensuring ongoing functionality.
• Monitors data processes, data flows, and scheduled jobs to ensure timely and accurate delivery of information.
• Performs root cause analysis and implements corrective actions to improve system stability and performance.
• Develops technical solutions to unique business and system challenges.
• Leads major projects, delegates tasks as appropriate, and ensures quality outcomes.

Data Process Automation

• Develops and implements automation solutions for data processing, validation, monitoring, reporting, and operational support activities.
• Identifies opportunities to improve efficiency, reduce manual intervention, and enhance process reliability.
• Supports CI/CD and deployment automation practices where appropriate.

Technical Documentation & Maintainability

• Creates and maintains technical documentation including data mappings, process flows, architecture diagrams, operational procedures, support documentation, and implementation plans.
• Ensures solutions are maintainable, supportable, and aligned with enterprise development standards and best practices.
• Reviews business specifications, technical designs, coding standards, testing plans, and implementation documentation for accuracy and completeness.

Planning & Team Ceremonies

• Participates in Agile planning activities, sprint ceremonies, backlog refinement, work estimation, and project execution activities.
• Collaborates with stakeholders to prioritize work and align solutions with business objectives.
• Provides technical leadership and guidance during project planning and delivery efforts.

Technical Expertise

• Utilizes expertise to mentor and train associates within the work group.
• Serves as a technical resource for management, associates, and business partners.
• Participates in special projects and meetings as needed to provide technical insight and recommendations.
• Promotes best practices related to data management, reporting, analytics, software development, and operational support.

Data Analysis

• Collects and analyzes data related to user requests and business requirements to determine scope, effort estimates, dependencies, and system impacts.
• Evaluates business and technical requirements to develop effective data and reporting solutions.
• Reviews specifications, coding, test plans, documentation, and implementation activities to ensure quality and alignment with business needs.

Required Technical Skills

• Advanced SQL development, query optimization, and performance tuning.
• Experience with Oracle database technologies and data warehouse environments.
• Advanced experience with ETL/ELT development and support.
• Advanced experience with Python or similar programming language used for automation, orchestration, and data engineering solutions.
• Experience with data ingestion, source integration, and API-based data acquisition.
• Knowledge of data warehousing concepts, methodologies, and best practices.
• Experience developing and maintaining analytics-focused and dimensional data models.
• Experience supporting historical data management and snapshot-based reporting.
• Experience implementing data quality controls, reconciliations, and validation processes.
• Experience with pipeline orchestration and automated workflow management.
• Experience with cloud-based data technologies, preferably AWS.
• Experience with monitoring, troubleshooting, observability, and production support processes.
• Advanced experience with Git or similar source code repository systems.
• Experience with CI/CD processes and deployment automation.
• Advanced experience with Jira, ServiceNow, or similar work management and support platforms.
• In-depth knowledge and experience with Software Development Life Cycle (SDLC) methodologies, including Agile and Waterfall.
• Proven ability to drive consensus among cross-functional roles, resolve conflicting situations, and drive effective business and technical outcomes.
• Ability to participate in an on-call support rotation as needed.