Data Solutions Engineer

Overview As a Data Solutions Engineer, you design and build enterprise data solutions that span analysis, modeling, architecture, engineering, and integration. You will collaborate with cross-functional teams to align data initiatives with the firm's enterprise data strategy and master data management goals. You’ll tackle data pipelines, quality, and governance at scale using a modern Azure-based stack. This role offers impact by centralizing transformations to deliver trusted, shareable data across the organization. Compensation / BenefitsCompetitive salaryPerformance bonusGenerous PTO401(k) retirement planHealth, dental, and vision insuranceWellness programs (BHealthy) ResponsibilitiesDevelop and implement data processing workflows and pipelines for solutions development and BI needsDesign scalable data solutions to enable data flow and integration across systemsLeverage Azure Data Factory, Synapse Analytics, and Data Factory for large-scale data processingBuild and maintain storage solutions (Azure SQL Database, PostgreSQL, Azure Data Lake, Azure Blob Storage)Support the Enterprise Data Model by managing the medallion architecture layers in the data lakeAdvance master data management and data modeling by centralizing transformations and business rulesImplement data validation and cleansing to ensure data quality and integrityUtilize Microsoft Fabric to support data engineering, analytics, and BI solutionsEmploy Microsoft Power Platform and Logic Apps to enable data integration, automation, and app development Key requirementsProficiency with Azure Data Factory, Azure SQL Database, PostgreSQL, Azure Blob Storage, Azure Data Lake StorageExperience with Azure Synapse Analytics, Azure Databricks, Apache Spark, Apache AirflowFamiliarity with Azure Logic Apps, Azure DevOps, Power Automate, REST APIKnowledge of data analysis, data modeling, data architecture, and master data managementMedallion architecture design patterns using Delta Lake (bronze, silver, gold)Experience with Microsoft Fabric (Lakehouse, Data Engineering, Real-Time Analytics)Experience with Microsoft Power Platform for low-code data integration and automationVersion control and CI/CD practices for data workflows (Azure DevOps, Git)Experience with unstructured data processing (Azure OpenAI, Document Intelligence)Strong communication of technical concepts to varied audiencesAbility to lead and build consensus among peers and staffEffective project management and time reportingAzure Data FactoryAzure SQL DatabasePostgreSQL