Data & Analytics Engineer

Primary Objective of Position

The data and analytics capabilities supporting Revelyst positioned in our Irvine, California office. This is a hands-on technical role responsible for developing and supporting data pipelines, data models, reporting solutions, and the underlying analytics environment that enables reliable business decision-making. This position will serve as a key technical resource for the enterprise data ecosystem, working across enterprise platforms including ERP, CRM, e-commerce/B2B, custom applications, and other operational data sources. The role will partner closely with Finance, business analysts, application teams, and external technology partners to ensure data is accessible, reliable, appropriately governed, and structured for reporting and analytics. The successful candidate will combine strong data engineering fundamentals, including hands-on Databricks and Spark experience, with working business intelligence experience and an interest in growing into broader data architecture and platform ownership responsibilities.

Key Responsibilities

• Design, develop, maintain, and support data pipelines and integrations across enterprise applications, APIs, databases, and cloud data platforms such as Databricks and Microsoft Fabric.
• Build and maintain scalable data models, transformations, and ETL/ELT processes that provide reliable, usable data for reporting and analytics.
• Implement pipeline orchestration, monitoring, alerting, and automated data-quality checks to keep production data flows reliable and observable.
• Develop and support Power BI datasets, semantic models, dashboards, and reports supporting Finance, Sales, Operations, Supply Chain, and other business functions.
• Monitor and support the Golf data and analytics environment, troubleshooting pipeline failures, reporting issues, performance problems, and data discrepancies.
• Identify data-quality and normalization issues and partner with business and application owners to improve data accuracy, consistency, and governance.
• Support and evolve the data architecture, including transitioning knowledge and ownership of the existing Microsoft Fabric environment from external partners.
• Partner with business analysts, application teams, and technology partners to translate business and reporting needs into scalable technical solutions.
• Identify opportunities to simplify and automate the data environment while helping build a foundation that supports future analytics, AI, and automation capabilities.

Minimum Qualifications

• 3+ years of experience in data engineering, business intelligence, analytics engineering, or a related technical role.
• Strong SQL skills and experience working with relational and analytical datasets.
• Experience with Git-based version control and engineering practices such as code review, CI/CD, and automated testing of data pipelines.
• Hands-on experience developing and supporting ETL/ELT pipelines, data transformations, and data models.
• Proficiency in Python for data engineering, transformation, and automation.
• Hands-on experience with Power BI, including data modeling, dashboards, reports, and semantic models.
• Experience working with a cloud data platform, data warehouse, lakehouse, or similar analytics environment.
• Experience integrating and working with data from multiple business systems, databases, APIs, or other data sources.
• Strong troubleshooting and problem-solving skills, including the ability to investigate data-quality, pipeline, reporting, and performance issues.
• Strong communication and collaboration skills with the ability to work effectively with both technical and business teams.
• Equivalent professional experience and demonstrated technical capability will be considered in place of formal education requirements.

Preferred Qualifications

• Experience with Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, or similar modern cloud data platforms.
• Experience integrating data from SAP or Oracle ERP, Salesforce CRM, e-commerce/B2B, and other enterprise business applications.
• Experience working with financial, sales, inventory, customer, supply chain, or other operational business data.
• Familiarity with Python or other scripting languages commonly used in data engineering and automation.
• Experience supporting production data and reporting environments, including monitoring, troubleshooting, and performance optimization.
• Exposure to data governance, data-quality management, AI/advanced analytics, or modern data architecture practices.
• Experience in working with Ecomm/subscriptions/software business model.

Key Soft Skills

• Strong analytical and problem-solving skills with a natural curiosity to understand how data, systems, and business processes connect.
• Proactive and resourceful, with the ability to independently investigate issues and drive solutions through completion.
• Strong attention to detail while maintaining an understanding of broader business objectives and priorities.
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