Cloud Data Engineer

Overview In this role, you will design and maintain scalable cloud-based data platforms that power enterprise analytics and reporting. You will work within a cross-functional team to implement lakehouse and data warehouse solutions on Azure, enabling secure, high-volume data processing. You’ll optimize SQL, PySpark, and Databricks workloads to deliver reliable data pipelines and analytics capabilities. You will also contribute to AI/ML initiatives by preparing data and supporting feature engineering and MLOps. This is an opportunity to shape data architecture and drive data-driven decision making at scale. Compensation / BenefitsMedical & Dental plansLife InsuranceFlexible Spending Accounts401kPaid Time Off ResponsibilitiesDesign, develop, and maintain ETL/ELT pipelines and analytics workflows using Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and SQLEvaluate modern cloud architectures and provide design alternatives with business and operational impactDevelop and optimize complex SQL, T-SQL, Spark SQL, and PySpark workloads focusing on performance, scalability, and cost efficiencyCode, test, deploy, and document Databricks notebooks (Python, PySpark, Spark SQL, Scala) and cloud-native data solutions using Git, CI/CD, and Azure DevOpsManage end-to-end development lifecycle for high-impact data initiatives including requirements, design, development, testing, deployment, and production supportSupport AI/ML and Generative AI initiatives by building data prep and feature engineering pipelines and scalable data platformsStay current with cloud, data engineering, AI, and analytics trends and propose innovative, value-driving solutionsCollaborate with stakeholders, architects, and leaders to translate requirements into scalable technical solutionsPerform related duties as assigned Key requirements7+ years of experience in cloud data engineering, ETL/ELT, data warehousing, and enterprise analyticsStrong experience with Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and data lakehouse architecturesProven experience implementing Medallion Architecture (Bronze/Silver/Gold) for scalable data pipelinesAdvanced Python, PySpark, Spark SQL, SQL, T-SQL, and Scala skills for developing and tuning large-scale workloadsExperience designing and tuning complex queries and data processing across high-volume datasetsExperience implementing CI/CD, Git-based source control, and Azure DevOps for automated deploymentsKnowledge of data warehousing concepts (dimensional modeling, star/snowflake schemas, governance, metadata, data quality)Experience supporting AI/ML initiatives including data prep, feature engineering, model integration, vectorized data architectures, and MLOpsBachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or related field, or equivalent work experienceStrong analytical and problem-solving abilities; effective communication with technical and non-technical stakeholdersAbility to work independently and collaboratively in a fast-paced environmentCommitment to continuous learning and staying current with new technologiescommunicationcollaborationproblem-solvingAzure DatabricksAzure Synapse AnalyticsAzure Data Factory