Senior Data Engineer

Role Overview

• Architect and implement enterprise-grade, cloud-based data platforms using Azure and Microsoft Fabric.
• Design scalable data Lakehouse architectures leveraging Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Microsoft Fabric (Lakehouse, Warehouse, Data Pipelines, Real-Time Analytics).
• Develop high-performance ETL/ELT pipelines using Azure Data Factory, Fabric Data Pipelines, SSIS, and PySpark.
• Implement distributed data processing solutions using Spark architecture and optimize Spark jobs for performance and cost efficiency.
• Lead cloud architecture design, including data ingestion patterns, medallion architecture (Bronze/Silver/Gold), governance frameworks, and CI/CD automation.
• Collaborate with cross-functional stakeholders to gather future-state requirements and translate business needs into technical solutions.
• Design and optimize complex SQL-based data models, star schemas, and enterprise semantic layers for analytics and reporting.
• Enable advanced analytics use cases using Python, R, machine learning frameworks, and Azure ML services.
• Support enterprise BI initiatives using Power BI, Fabric Semantic Models, and Power Automate.
• Participate in on-call rotations to support mission-critical production systems.
• Drive modernization initiatives from legacy MSBI environments to cloud-native and Fabric-based ecosystems On call rotation and availability outside of normal business hours to support a 24x7x365 environment

Requirements

• 10+ years of progressive IT experience with strong specialization in Data Engineering, Enterprise Data Warehousing, and Analytics platforms.
• 5+ years of deep, hands-on experience with Data Warehouse architecture, dimensional modeling, ETL/ELT frameworks, and enterprise BI solutions.
• Strong expertise in Microsoft BI stack including SQL Server, SSIS, and advanced T-SQL development and performance tuning.
• Advanced programming proficiency in SQL, Python, and PySpark with solid understanding of distributed computing and Spark architecture concepts (execution model, partitioning, optimization strategies).
• Proven experience building and optimizing cloud-native data solutions using: Azure Synapse Analytics Azure Data Factory Azure Data Lake Storage Azure Databricks Azure Logic Apps Microsoft Fabric (Lakehouse, Data Pipelines, Warehouse, Semantic Models)
• Strong experience designing scalable, secure, and cost-efficient cloud data architectures across hybrid and multi-source environments.
• Working knowledge of modern data platform patterns including lakehouse architecture, medallion layering, data governance, and CI/CD practices.
• Exposure to Data Science and advanced analytics technologies (Python, R, machine learning algorithms, Azure ML) preferred.
• Experience with Microsoft Power Platform tools including Power BI and Power Automate preferred.
• Strong analytical, problem-solving, and troubleshooting skills with the ability to navigate complex enterprise data landscapes.
• Self-driven professional with excellent communication skills and ability to collaborate across technical and business teams.
• Comfortable working in high-priority, time-sensitive environments with on-call support responsibilities.
• Bachelor’s or Masters degree in Computer Science, Data Science, Information Systems, Engineering, or related field (or equivalent practical experience).

Tech Stack

• Azure
• Cloud
• ETL
• PySpark
• Python
• Spark
• SQL
• SSIS

Benefits

• Continuous professional development opportunities and an environment that fosters internal growth and mobility.
• Competitive compensation and benefits package which includes multiple healthcare options, tuition reimbursement, and matching 401k.
• Generous holiday schedule and paid time off to refresh and recharge.
• Employee pricing on our products and discount programs for travel, entertainment, and more!