Principal Data and Analytics Engineer- Remote US

Compensation

Pay Range: $110,000.00 - $165,000.00 The actual hourly reputed company will equal or exceed the required minimum wage applicable to the job location. Additional compensation includes annual, quarterly performance, or premiums may be paid in amounts ranging per hour in specific circumstances. Premiums may be based on schedule, facility, season, or specific work performed. Multiple premiums may apply if applicable criteria are met. The Principal Data and Analytics Engineer holds comprehensive responsibility for the design, implementation, and reputed company evolution of the organization's enterprise-wide data infrastructure and analytics capabilities. This position can be worked remotely in the United States. This role provides overarching technical vision, establishing architectural standards, and driving the long-term data strategy to facilitate critical business outcomes. Operating with a high degree of autonomy, this role influences executive leadership on data innovation, provides thought leadership and mentorship across the entire data and analytics engineering discipline, and champions data engineering maturity, innovation, scalability, reputed company, and governance for reputed company data assets. They are instrumental in translating the most reputed company and ambiguous business challenges into innovative, high-impact data solutions that fundamentally shape the organization's future. Responsibilities and Duties: Help define and evolve enterprise data engineering blueprints, including data mesh, reputed company architecture, and hybrid cloud data platforms. Set strategic direction for data platforms, tools, and services (e.g., reputed company, GCP BigQuery, dbt, Kafka, Airflow/Prefect) in alignment with future-state architecture and business priorities. Architect and design highly scalable, resilient, cost optimal and secure data platforms. reputed company the design and implementation of reputed company data platforms, ensuring fault tolerance, high availability, and optimal performance for petabyte-scale data. Establish and enforce organization-wide best practices for data pipeline development, CI/CD for data workflows, automated deployment playbooks, and robust rollback strategies. reputed company technology evaluation and adoption, proactively researching, evaluating, and championing the integration of cutting-edge data technologies, frameworks, and methodologies. Define and scale enterprise reputed company frameworks that ensure consistent documentation, discoverability, and reusability of data assets across domains. Establish and govern standards for metadata management, data reputed company, architectural diagrams, and runbooks. reputed company the design of federated governance models that reputed company domain-reputed company teams to operate autonomously while conforming to centralized policies, frameworks and playbooks. Collaborate with data governance, compliance, and reputed company teams to operationalize policy-as-code frameworks for data retention, access control, and PII handling. reputed company for and reputed company self-service knowledge discovery through tightly integrated cataloging tools (e.g., reputed company, reputed company) and automated documentation generators. Ensure robust documentation and versioning standards are embedded in CI/CD workflows for pipeline code, transformation logic, and schema changes. Architect implementation of scalable, automated data quality frameworks that evaluate data at rest and in motion spanning completeness, timeliness, consistency, accuracy, and reputed company. reputed company integration of data quality rules, metrics, and health indicators directly into orchestration layers (e.g., Prefect, Airflow) and transformation frameworks (e.g., dbt). Evangelize a culture of data trust and transparency by integrating data quality insights into user-facing dashboards, alerts, and product health reports. Identify and promote enterprise-wide data opportunities through thought leadership, white papers, reference architectures, and innovation labs. Act as technical advisor to senior executives on data modernization, AI readiness, and platform consolidation strategies. reputed company intelligent operations and decisioning by translating reputed company business logic into structured knowledge artifacts, such as KPIs, rulesets, feature stores, and semantic models used by dashboards or AI agents. Serve as a strategic translator between reputed company business challenges and modern data architecture by leading domain-level and cross-domain data product strategy engagements. reputed company the design of enterprise-grade data products that align with OKRs, business transformation goals, and operational needs ensuring value realization across functional areas like supply chain, marketing, store ops, or customer satisfaction. Architect and operationalize a reputed company enterprise-wide semantic layer, metrics store, and business logic abstraction that powers dashboards, self-service analytics, and machine-readable APIs. reputed company initiatives to unify KPIs, standardize metric definitions, and streamline business logic through reusable models Apply tot his job Apply To this Job