Lead Data Engineer

Role Overview

• Lead the architecture, engineering, and stabilization of the centralized Finance reporting data platform supporting enterprise Finance reporting and analytics initiatives.
• Design and implement scalable Databricks lakehouse solutions utilizing Bronze/Silver/Gold (Medallion) architecture patterns to support Finance reporting, month-end close processes, and analytical workloads
• Develop and optimize advanced Databricks notebooks, workflows, Delta Lake pipelines, and orchestration frameworks to ingest, transform, validate, and operationalize large-scale Finance datasets.
• Engineer reporting-ready analytical datasets and dimensional models optimized for enterprise Power BI reporting, semantic models, and governed self-service analytics
• Develop advanced SQL-based transformation logic, financial aggregations, reconciliations, and reporting datasets utilizing Databricks SQL and Snowflake capabilities
• Design and maintain scalable star schema and curated reporting layer structures supporting financial hierarchies, KPI standardization, P&L reporting, variance analysis, and executive reporting requirements.
• Establish and maintain standardized financial hierarchies, mappings, and metric definitions across business lines, ensuring consistency across reporting outputs
• Lead month-end Finance data operationalization processes, including ingestion, snapshot management, reconciliations, validation controls, auditability, and close-cycle reporting readiness.
• Implement enterprise-grade data quality, lineage, monitoring, validation, and change management frameworks to ensure financial data accuracy, traceability, and governance compliance
• Partner with FP&A, Accounting, Reporting & Analytics leadership, and enterprise data teams to translate Finance reporting requirements into scalable data and reporting platform solutions.
• Provide technical leadership and architectural guidance across Finance data platform initiatives, establish engineering standards and best practices, and oversee vendor/offshore delivery execution.

Requirements

• Bachelor's degree in Information Systems, Computer Science, Analytics, Finance, or related field
• 6+ years of experience in data engineering, BI data architecture, or analytics platforms
• 3+ years of leadership experience leading data/BI engineering projects or platforms
• 2+ years of people leadership experience with direct reports
• Advanced SQL expertise for large-scale data transformation, modeling, and performance optimization
• Advanced hands-on experience with Databricks engineering, including Spark, PySpark, Delta Lake, notebooks, workflows, and orchestration.
• Strong understanding and practical implementation experience with Medallion Architecture (Bronze/Silver/Gold) and lakehouse design patterns.
• Advanced SQL expertise, including complex transformations, performance optimization, window functions, dimensional modeling, and large-scale financial data processing.
• Strong Power BI experience, including semantic model design, star schema modeling, dataset optimization, DAX understanding, and enterprise reporting enablement.
• Experience designing curated analytical datasets optimized for reporting and self-service analytics consumption.
• Experience operationalizing month-end Finance reporting processes, reconciliations, data validations, and close-cycle reporting support.
• Experience working with Snowflake and cloud-based enterprise data platforms.
• Strong stakeholder partnership experience with Finance, FP&A, Accounting, and Reporting organizations.

Tech Stack

• Cloud
• PySpark
• Spark
• SQL

Benefits

• medical, dental and vision benefits
• 401(k) retirement savings plan
• time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)
• short-term and long-term disability
• life insurance
• many other opportunities