Senior Data Engineer

Experteer Overview As a Senior Data Engineer at MMA, you will design and maintain scalable data pipelines and data models to empower data-driven decision-making across the organization. You will collaborate with the National IT Team to leverage Azure cloud solutions (Databricks, ADF, etc.) and build enterprise data warehouses with robust governance. You will tackle data quality, security, and real-time as well as batch processing challenges, shaping the data platform for business impact. This role offers meaningful work in a inclusive, top-workplace culture with growth around cloud-native analytics and AI enablement. Compensation / Benefits * Develop and maintain scalable data pipelines and data models in Azure cloud solutions * Provide SME for data acquisition, consumption, and governance across ETL/ELT processes * Design and implement enterprise data warehouse platforms and reusable data engineering libraries * Work with Databricks, ADF, Spark, SQL, Delta Lake, and other tools to optimize performance * Enable real-time and batch data processing using Kafka or Event Hub * Support ML/AI workflows on Databricks and deploy conversational analytics on custom datasets * Implement CI/CD and IaC practices (Azure DevOps, Git, Terraform, ARM templates) * Ensure data quality, security, and compliance across the data lifecycle * Foster collaboration across cross-functional teams to align with business objectives * Leverage Unity Catalog for data governance and access control Tasks * 10+ years of practical data engineering experience in enterprise settings * Strong proficiency with Azure Databricks, Azure Functions, and Azure Data Factory (preferred) * Advanced PySpark, Python, Databricks SQL skills with performance tuning * Deep experience with ETL/ELT, data pipelines, orchestration and scheduling * Delta Lake features such as CDC, ACID, optimization, and schema evolution * Solid data modeling skills (normalized, dimensional, Lakehouse) * Experience with batch and real-time processing (Kafka, Event Hub) * Understanding of data architecture, distributed systems, and cloud-native design * Knowledge of data governance, security, and Unity Catalog * Experience with CI/CD, IaC (Terraform, ARM), and DevOps * Insurance and healthcare data domain experience is a plus * Databricks and Azure certifications a plus Key requirements * remote work * generous time off * tuition reimbursement and professional development * stock purchase opportunities * charitable contribution match * 401K and retirement programs

Spark, performance * Enable real-time and batch data processing using Kafka or Event Hub * Support ML/AI workflows on Databricks and deploy conversational analytics on custom datasets * Implement CI/CD and IaC practices (Azure DevOps, Git, Terraform, ARM templates) * Ensure data quality, security, and compliance across the data lifecycle * Foster collaboration across cross-functional teams to align with business objectives * Leverage Unity Catalog for data governance and access control Tasks * 10+ years of practical data engineering experience in enterprise settings * Strong proficiency with Azure Databricks, Azure Functions, and Azure Data Factory (preferred) * Advanced PySpark, Python, Databricks SQL skills with performance tuning * Deep experience with ETL/ELT, data pipelines, orchestration and scheduling * Delta Lake features such as CDC, ACID, optimization, and schema evolution * Solid data modeling skills (normalized, dimensional, Lakehouse) * Experience with batch and real-time a real-time (Kafka, Event Hub) * Understanding of data architecture, distributed systems, and cloud-native design * Knowledge of data governance, security, and Unity Catalog * Experience with CI/CD, IaC (Terraform, ARM), and DevOps * Insurance and healthcare data domain experience is a plus * Databricks and Azure certifications a plus Key requirements * remote work * generous time off * tuition reimbursement and professional development * stock purchase opportunities * charitable contribution match * 401K and retirement programs