Principal Data Engineer I

At Meazure Learning , we aim to empower open-minded, inquisitive, and driven people, and we love how each new addition to the team adds to our culture. Here, you can positively impact the careers of millions of test-takers and reshape the education technology landscape by working toward one vision: “To provide life-long learners across the globe the freedom to pursue their academic dreams and career aspirations safely, securely, and conveniently.” Our Vision starts with our values— Hungry, Humble, and Smart. We are looking for team members who model drive for results, think of the organization and team first without ego or agenda, and lead with emotional intelligence. This is the foundation of success for all employees at Meazure Learning. The Role: The Principal Data Engineer I will play a key role in building and maintaining the infrastructure and architecture that supports the company’s data and analytics needs. You will design, implement, and maintain scalable data pipelines, systems, and workflows while collaborating with other teams to ensure that the data infrastructure meets the needs of various business functions. As a senior leader in the data engineering team, you will set the standards for best practices and will be a mentor to other data engineers. The Responsibilities: Define and lead enterprise data architecture strategy with strong focus on Azure-based modern data platforms and Lakehouse architecture. Architect, design, and optimize scalable Data Warehouse and analytics solutions using Azure Synapse, Azure Data Lake Storage Gen2, Databricks, Delta Lake, and Microsoft Fabric. Build and orchestrate robust ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, PySpark, and modern orchestration frameworks. Implement Medallion Architecture (Bronze/Silver/Gold) and scalable data ingestion frameworks supporting batch, streaming, and CDC workloads. Develop enterprise semantic models and optimize datasets for Power BI Premium, Fabric, and self-service analytics. Establish enterprise standards for data modeling, governance, security, observability, and performance optimization. Lead Data Warehouse modernization initiatives and implement scalable Star Schema, Snowflake, and Data Vault 2.0 models. Drive platform scalability, MPP query tuning, workload optimization, and cloud cost optimization initiatives. Implement CI/CD, DataOps, and Infrastructure-as-Code practices using Azure DevOps, GitHub Actions, Terraform, or Bicep. Promote AI-assisted engineering practices leveraging GitHub Copilot, Cursor AI, and Azure OpenAI for development productivity and automation. Mentor engineering teams and drive engineering excellence, automation, and reusable framework adoption. Data Engineering & Modeling: Strong expertise in enterprise Data Warehouse and Lakehouse architecture. Advanced SQL, MPP performance tuning, and distributed data processing experience. Hands-on expertise in Python, PySpark, and SQL for large-scale transformations. Strong knowledge of: Medallion Architecture Star/Snowflake Schema Data Vault 2.0 Semantic Modeling DevOps / DataOps : Experience implementing CI/CD pipelines using Azure DevOps or GitHub Actions. Infrastructure-as-Code experience using Terraform, ARM Templates, or Bicep.