Data Engineer, Scaling Analytics

Key Responsibilities

• Design, build, and maintain scalable data pipelines supporting infrastructure deployment, operations, capacity planning, and supply chain functions.
• Develop trusted datasets and reporting systems that provide visibility into hardware inventory, deployment status, site readiness, capacity utilization, and operational performance.
• Partner with cross-functional stakeholders to define metrics, establish data standards, and improve decision-making across infrastructure organizations.
• Create scalable data models that enable consistent reporting and analytics across multiple data sources and operational systems.
• Improve data quality, lineage, observability, and governance practices across critical infrastructure datasets.
• Support executive reporting, operational reviews, forecasting exercises, and strategic planning initiatives through reliable analytical foundations.
• Collaborate with engineering teams to integrate new data sources and operational telemetry into existing analytics ecosystems.
• Build solutions that reduce manual reporting efforts and improve the speed and accuracy of infrastructure decision-making.
• Document systems, processes, and analytical frameworks to improve long-term maintainability and organizational resilience.

Qualifications

• 5+ years of experience building and maintaining production data pipelines and analytical systems.
• Strong proficiency in SQL and experience designing scalable data models.
• Proficiency in Python or another programming language commonly used for data engineering.
• Experience working with modern data warehouses (e.g., Snowflake, BigQuery, Redshift) and orchestration frameworks (e.g., Airflow, Dagster).
• Experience designing reliable ETL/ELT workflows with a focus on maintainability, performance, and operational excellence.
• Experience partnering with cross-functional stakeholders to translate business requirements into technical solutions.
• Experience implementing data quality checks, monitoring, and observability practices in production environments.

Preferred Skills

• Experience supporting infrastructure, hardware operations, supply chain, manufacturing, logistics, or capacity planning organizations.
• Familiarity with large-scale operational telemetry and business-critical reporting environments.
• Experience with distributed processing frameworks such as Spark.
• Experience with transformation frameworks such as dbt.
• Experience developing executive reporting and operational review metrics.
• Experience operating in fast-paced, ambiguous environments with evolving priorities.