Senior Data Engineer

Role Description

The Senior Data Engineer will join the Americas IT software and architecture team. This business-centric IT team enables business-focused development of cutting-edge solutions and integrates global/regional IT initiatives into the business.

In this senior role, we are seeking an experienced Data Engineer with deep hands-on expertise in Apache Spark, Microsoft Fabric, and cloud-scale data architecture. You will lead the design of robust data pipelines, optimize large-scale data architectures, and drive data-driven decision-making across the organization.

The Senior Data Engineer is expected to work independently, collaborate with business and IT leaders, guide junior engineers, and architect solutions from the ground up based on complex business requirements.

Key Responsibilities

• Design and Develop Enterprise Data Pipelines: Architect, build, and maintain scalable, distributed data pipelines leveraging Apache Spark and Microsoft Fabric to process large structured and unstructured datasets.
• Data Integration Leadership: Integrate data from diverse internal and external systems, ensuring reliability, lineage, and consistency across the enterprise.
• Performance Optimization: Lead optimization of ETL/ELT workloads for large-scale analytics, improving cost efficiency, throughput, and reliability.
• Data Quality & Governance: Define and implement standards for data quality, metadata management, cataloging, lineage, and governance compliance.
• Cross-Functional Collaboration: Partner with data scientists, analysts, architects, and IT teams to define requirements, deliver insights, and integrate analytical models.
• Documentation: Develop and maintain in-depth documentation for pipeline architectures, workflows, schemas, and operational processes.
• Continuous Innovation: Evaluate emerging technologies and introduce modern data engineering practices such as lakehouse patterns, delta formats, automation, and real-time processing.
• Troubleshooting & Reliability: Lead resolution of complex data pipeline failures, ensuring platform stability and enterprise-grade reliability.
• Security & Compliance: Enforce enterprise data security, privacy, and access governance policies.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field.
• 7+ years of professional experience in data engineering, data architecture, or large-scale data platform development.
• Expertise in Apache Spark for large-scale batch and streaming workloads.
• Deep hands-on experience with Microsoft Fabric, including Data Engineering, Data Factory, Data Pipelines, and Lakehouse implementations.
• Advanced proficiency in SQL, Python, and/or Scala.
• Hands-on expertise with Microsoft Azure (preferred), AWS, or GCP cloud data services.
• Strong understanding of distributed systems, lakehouse patterns, and data modeling.
• Proven experience designing and optimizing complex ETL/ELT workflows.
• Strong communication skills, leadership capability, and technical mentorship experience.

Preferred Qualifications

• Professional certifications in Azure Data Engineering, Apache Spark, or Microsoft Fabric.
• Experience with real-time streaming technologies such as Kafka or Azure Event Hubs.
• Knowledge of DevOps practices including CI/CD, Infrastructure as Code, and automated testing.
• Experience with visualization tools such as Power BI or Tableau.

Benefits

• Competitive compensation and an outstanding benefits package.
• Access to health, dental, disability, and life insurance.
• Paid holidays and vacation.
• 401(k) matching and pension benefits.
• Employee discount program.
• Opportunities for educational and professional growth.

Salary

Pay commensurate with experience. Open to salary range $108,225 - $158,730.