Principal Data Engineer

🏢 Industry: IT services and IT consulting 💼 Work Setting: HybridAre you passionate about building trusted data platforms, enabling self-service analytics at scale, and transforming complex enterprise data into strategic business insights? We are seeking a Data Engineer to design, develop, and maintain scalable data platforms that empower business and engineering teams with reliable, actionable data. This role combines data engineering, analytics enablement, data modeling, and stakeholder partnership to build high-quality data products that support operational excellence and strategic decision-making across cloud infrastructure environments.

Data Engineering & Platform Development: Design, develop, test, document, and maintain scalable data engineering solutions and analytics platforms. Build and optimize SQL-based ETL/ELT pipelines that support large-scale reporting and analytical workloads. Develop reusable data models, curated datasets, and enterprise data assets that serve as trusted sources of truth. Create and maintain canonical datasets that support operational, financial, and strategic decision-making. Ensure solutions are scalable, maintainable, performant, and aligned with engineering best practices.

Data Architecture & Modeling: Design and implement data warehouse solutions and dimensional data models. Establish data standards, business rules, metadata frameworks, and lineage documentation. Define transformation logic and ensure consistency across datasets and reporting solutions. Support enterprise-wide data governance initiatives and data quality improvement programs.

Business Partnership & Analytics Enablement: Collaborate with engineering, finance, product, operations, and business stakeholders to understand requirements and deliver scalable solutions. Translate ambiguous business challenges into structured data models and analytical solutions. Support the development of self-service reporting and analytics capabilities. Clearly communicate technical concepts, data assumptions, lineage, and business rules to both technical and non-technical audiences.

Operational Excellence & Continuous Improvement: Own projects from requirements gathering through production deployment and ongoing support. Monitor data quality, accuracy, reliability, and performance across data pipelines and reporting solutions. Identify opportunities to automate manual processes and improve operational efficiency through data-driven approaches. Contribute to documentation, governance practices, engineering standards, and knowledge-sharing initiatives. Participate in continuous improvement efforts that enhance platform reliability and stakeholder experience.

Preferred Qualifications: Experience supporting cloud infrastructure, capacity planning, operations analytics, or distributed systems environments. Experience building self-service analytics platforms and reporting ecosystems. Familiarity with modern cloud-native data architectures and data engineering technologies. Experience working with large, complex datasets in fast-paced technology organizations. Passion for developing trusted data products that drive measurable business outcomes.