Senior Data Engineer

We're looking for a Senior Data Engineer to join our Data & Analytics team and play a key role in shaping the future of our enterprise Data Platform.

This role combines hands-on engineering with platform thinking. You will design and build scalable, high-performance data solutions while influencing the architecture, engineering standards, and long-term evolution of our Lakehouse platform.

Beyond developing data pipelines, you'll help establish best practices, improve platform reliability and scalability, and drive technical excellence across our Data Engineering ecosystem.

What you'll do

As a Senior Data Engineer, you will:

• Design, build, and evolve core components of our enterprise Lakehouse Data Platform.
• Develop scalable, reliable, and cost-efficient ELT pipelines supporting reporting, analytics, and AI/ML use cases.
• Design reusable data models and analytical layers that enable trusted, high-quality data across the organization.
• Contribute to architectural decisions related to data integration, storage, and data access patterns.
• Optimize platform performance, scalability, reliability, and operational costs.
• Define and promote engineering standards, integration patterns, automation, and Data Engineering best practices.
• Ensure data quality, security governance, and compliance through monitoring, validation, and access controls.
• Support Data Governance initiatives, including metadata management and Unity Catalog.
• Collaborate closely with business stakeholders, data architects, analysts, and IT teams to translate business requirements into scalable technical solutions.
• Act as a technical leader for selected Data Platform initiatives, mentoring team members and driving engineering excellence.

What we're looking for

You combine strong engineering skills with a platform mindset. You don't just build data pipelines—you design solutions that are scalable, maintainable, secure, and built for long-term success.

You bring:

• 5+ years of experience in Data Engineering, including designing and operating enterprise-grade data platforms.
• Strong expertise in Python, PySpark, SQL, Terraform, YAML, and Databricks Asset Bundles.
• Hands-on experience with Apache Spark, Databricks, Delta Lake, and processing large-scale datasets.
• Solid knowledge of Azure Data Services, including Azure Databricks, Azure Data Factory, ADLS, Unity Catalog, Azure DevOps, and Azure Event Hub.
• Experience orchestrating data workflows using Apache Airflow.
• Practical knowledge of Lakehouse architecture, Medallion architecture, and modern data modeling practices.
• Experience implementing CI/CD pipelines for data solutions using Azure DevOps.
• Strong understanding of code reviews, automated testing, deployment automation, and engineering best practices.
• Experience with Data Quality, metadata management, data cataloging, and access governance.
• The ability to translate business requirements into scalable technical solutions.
• Strong communication skills and confidence in leading technical discussions, influencing architectural decisions, and mentoring other engineers.

Nice to have

• Experience with Databricks LakeFusion or Microsoft Fabric (Data Engineering).
• Experience with Databricks DQX or other enterprise data quality frameworks.
• Databricks or Data Engineering certifications.

You’ll have the opportunity to shape a modern enterprise Data Platform that supports analytics, AI, and digital transformation across the organization. Your work will directly influence how data is managed, governed, and consumed, while helping establish engineering standards that enable scalable, secure, and high-quality data solutions for years to come.