Principal Data Engineer

• Provide technical leadership and hands‑on engineering expertise for Enterprise Data and Analytics Modernization initiatives across data engineering, analytics, reporting, and data consumption
• Design, develop, and optimize scalable batch, near real‑time, and real‑time data pipelines using Spark, Python, SQL, Databricks, Microsoft Fabric, Azure Data Factory, and related Azure cloud services
• Modernize legacy Analytical Data Store and BI workloads by migrating fragmented reporting and data assets into secure, standardized, governed, and cloud‑native analytics platforms
• Lead API‑driven and event‑based data onboarding patterns using Gravitee, Mule Soft, Kafka, and related technologies
• Establish reusable engineering ETL frameworks, design patterns, and automation for ingestion, transformation, validation, reconciliation, monitoring, and production support
• Implement automated data quality validation, reconciliation controls, exception handling, alerting, monitoring, SLA management, and production readiness practices
• Enable metadata management, lineage, cataloging, and access governance through Unity Catalog, Alation, and related governance capabilities
• Partner with data architects, analysts, product owners, business stakeholders, governance teams, and platform teams to translate business needs into scalable technical solutions
• Guide engineering teams through architecture reviews, implementation decisions, coding practices, design standards, performance tuning, and operational resilience improvements
• Ensure compliance with engineering, information security, data governance, and regulatory expectations
• Support Agile delivery, Dev Sec Ops , CI/CD deployment, release readiness, defect resolution, and production support
• Mentor senior and mid‑level engineers, promote engineering excellence, and drive adoption of enterprise standards

• Bachelor’s degree in information systems, Computer Science, Engineering, Data Engineering, or a related field, or the equivalent combination of education, training, and experience
• Advanced hands‑on expertise in Spark, Python, SQL, Databricks, Azure Data Factory, Microsoft Fabric, and cloud‑native data integration, transformation, and analytics solutions
• Strong experience designing, building, and supporting scalable data pipelines, lakehouse architecture, data warehouses, data marts, and analytical data stores
• Expertise in automated data quality validation, data reconciliation, metadata management, lineage, monitoring, alerting, error handling, and SLA management
• Experience with governance and catalog platforms such as Unity Catalog, Alation, or similar tools
• Experience with BI and analytics platforms such as Power BI, Tableau, Microsoft Fabric, and enterprise reporting modernization patterns
• Working knowledge of Azure Dev Ops, CI/CD pipelines, Agile delivery, production deployment, and operational support practices
• Ability to communicate complex technical concepts clearly to business stakeholders, technology leaders, engineers, and cross‑functional delivery teams
• Strong problem‑solving skills, architectural judgment, ownership mindset, and ability to lead delivery in complex, highly regulated enterprise environments
• Applicants must be authorized to work in the United States without the need for current or future sponsorship
• Ability to work Monday–Friday, 8:00AM–4:30PM

Demonstrates advanced expertise in designing and optimizing scalable data pipelines and cloud‑native analytics solutions using Spark, Python, SQL, and Azure services. Proven ability to lead technical teams, implement data governance practices, and ensure compliance in complex enterprise environments.

• Spark
• Python
• SQL
• Azure Data Factory
• Data Governance

• Data Engineering
• Data Pipeline Development
• Automated Data Quality Validation
• Metadata Management
• Data Reconciliation
• Lakehouse Architecture
• Data Warehousing
• Analytical Data Stores
• ETL Frameworks
• API‑Driven Data Onboarding

• Problem‑Solving
• Communication
• Leadership
• Mentoring
• Architectural Judgment

• Agile Delivery
• Dev Sec Ops
• CI/CD
• Data Governance
• Regulatory Compliance

• Databricks
• Microsoft Fabric
• Gravitee
• Mule Soft
• Kafka
• Unity Catalog
• Alation
• Power BI
• Tableau
• Azure Dev Ops