Data Engineer/Architect for SaaS

**Job Description:** Join our team to collaborate with software engineering, product, analytics, and business stakeholders in delivering high-performance data solutions for operational reporting, business intelligence, advanced analytics, and AI initiatives. **Key Responsibilities:** **Data Architecture & Platform Design** - Evolve data architecture for operational and analytical workloads. - Implement scalable data warehouses, lakes, and lakehouses. - Establish data modeling standards and best practices. - Modernize data platforms using Azure cloud technologies. **Data Engineering** - Develop and maintain scalable ETL/ELT pipelines. - Build data integration solutions using Azure services. - Ensure data quality through monitoring and automation. **Performance & Optimization** - Optimize SQL queries and data pipelines for efficiency. - Analyze large datasets to improve performance. - Collaborate with engineering teams to enhance database design. **Data Quality & Reconciliation** - Establish data validation and auditing processes. - Resolve data discrepancies across systems. - Maintain data quality standards. **Analytics Enablement** - Support data models for reporting and analytics. - Collaborate with stakeholders to translate requirements into solutions. - Enable self-service analytics through well-governed datasets. **Required Qualifications** - 7+ years in Data Engineering/Architecture. - Expertise in enterprise-scale data architectures and SQL. - Experience with ETL/ELT in cloud environments. - Strong understanding of data warehousing and governance. **Technical Skills** - Required: Azure SQL, Data Factory, Synapse Analytics, SQL Server, data modeling, and performance tuning. - Preferred: Microsoft Fabric, Azure Data Lake, Apache Spark, Python, CI/CD, and AI/ML data platforms. **Preferred Experience** - Experience with SaaS and large-scale datasets, particularly in data-intensive industries like healthcare. - Designing platforms for advanced analytics and business intelligence. **Success Metrics** - Reliable and scalable data platforms. - Trusted reporting with strong data quality. - High-performance environments that support business growth and analytics initiatives.