Transform Enterprise Data. Build the Future of Analytics.
We're looking for a Senior Data Analytics Engineer to lead the evolution of our next-generation data ecosystem.
This is a highly visible individual contributor role.
Responsibilities
Lead Enterprise Data Modernization Initiatives: Drive the migration of legacy reporting and analytics environments to modern cloud-based platforms.
Analyze existing BI models, SQL workloads, and reporting logic to identify optimization opportunities.
Convert complex business and reporting logic into scalable cloud-native data solutions.
Ensure data quality, accuracy, and seamless transition through comprehensive validation and testing.
Design & Build Scalable Data Platforms: Develop, enhance, and maintain enterprise-grade data pipelines and data products.
Build efficient data transformation frameworks using modern analytics engineering practices.
Optimize data models, processing frameworks, and reporting performance.
Establish scalable solutions that support future analytics, reporting, and machine learning initiatives.
Partner with Business & Analytics Leaders: Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions.
Serve as a trusted advisor on data architecture, reporting strategy, and platform capabilities.
Support strategic and ad hoc analytics requests through reliable, well-governed data assets.
Communicate technical concepts effectively to both technical and non-technical audiences.
Drive Operational Excellence: Implement best practices for data governance, version control, documentation, and deployment.
Monitor platform performance and proactively identify optimization opportunities.
Contribute to continuous improvement initiatives across analytics and data engineering functions.
Requirements
Bachelor's degree in Computer Science, Information Technology, Data Analytics, Engineering, or a related field.
4+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or Data Platform Development.
Strong expertise in SQL, including advanced query development, optimization, and stored procedure logic.
Experience working with Power BI, semantic models, and DAX-based reporting environments.
Hands-on experience with Spark, PySpark, Spark SQL, or similar big data technologies.
Proficiency in Python for data processing, automation, and analytics.
Experience using Git and modern software development practices.
Strong stakeholder management and requirements-gathering skills.
Excellent verbal and written English communication skills.
Preferred: Experience with Databricks, Delta Lake, Databricks SQL, DLT Pipelines, and Unity Catalog.
Preferred: Experience leading or contributing to cloud migration and data modernization initiatives.
Preferred: Knowledge of modern data warehousing, lakehouse architecture, and analytics platforms.
Preferred: Databricks, Azure, AWS, or related cloud certifications.
Preferred: Experience supporting high-volume, customer-facing, or enterprise-scale operations.
Preferred: Exposure to analytics, machine learning, or data science environments.