Senior Data Engineer

Foundation Partners Group is dedicated to helping families create meaningful goodbyes during their most vulnerable moments. They are seeking a Senior Data Engineer to design, build, and operate modern data platforms at scale, working across cloud-native Azure infrastructure and AWS, to develop reliable data pipelines and analytics that support business decisions.

Responsibilities:

• Design and build scalable data pipelines using Python and cloud-native orchestration tools, including Azure Data Factory, Azure Container Apps Jobs, and Fabric Data Pipelines
• Architect data solutions across Microsoft Fabric Warehouses, Azure SQL Database, and AWS (S3, Redshift), selecting the right tool for the workload
• Implement Medallion/layered architecture patterns (Bronze to Silver to Gold) for structured, governed data delivery
• Manage and optimize large-scale data warehouse environments with a focus on performance, cost, and maintainability
• Develop Python-based ETL/ELT pipelines to ingest and transform data from APIs, flat files, databases, and SaaS platforms
• Build and deploy containerized pipeline jobs using Azure Container Apps Jobs, including scheduling, scaling rules, secrets management via Azure Key Vault, and integration with Azure Container Registry
• Build and maintain data movement between on-premises SQL Server environments and cloud targets
• Design idempotent, fault-tolerant pipeline patterns with robust logging, alerting, and retry logic
• Collaborate with analytics and reporting teams to deliver clean, well-documented data models for Power BI or similar BI tools
• Manage data infrastructure across Azure (Fabric, Azure SQL, Azure Data Lake, Key Vault, Container Apps, Container Registry) and AWS (S3, EC2, RDS/Redshift)
• Containerize data workloads using Docker; deploy and operate them as Azure Container Apps Jobs for scheduled batch processing and event-triggered pipeline execution
• Implement infrastructure-as-code principles and version-controlled deployment practices using GitHub, Bicep or Terraform, and CI/CD tooling (Azure DevOps or GitHub Actions)
• Monitor platform health, optimize compute and storage costs, and enforce data security and access governance
• Partner with data analysts, BI developers, software engineers, and business stakeholders to translate requirements into technical solutions
• Maintain thorough technical documentation: pipeline specs, data dictionaries, runbooks, and architecture diagrams
• Champion engineering best practices: code reviews, testing, modular design, and reusable frameworks
• Mentor junior engineers and contribute to team standards and knowledge sharing

Requirements:

• Python: fluent in writing production-grade pipelines, data transformations, and automation scripts
• RDBMS: Advanced T-SQL and/or ANSI SQL; experience with SQL Server, Azure SQL DB, and cloud warehouse query engines (Redshift, Fabric)
• MS Fabric: Warehouses, Lakehouses, Data Pipelines, OneLake, and Fabric's unified analytics model
• Azure ecosystem: Azure Data Factory, Azure SQL Database, Azure Data Lake Storage, Azure Key Vault, Azure Container Apps Jobs, Azure Container Registry, and related services
• Containerization: Docker image development, container registry management, and deploying workloads as Container Apps Jobs with schedule and event triggers, scaling rules, and environment variable/secret injection
• AWS data services: S3 for data lake storage, Redshift for cloud data warehousing
• Data modeling: dimensional modeling, star/snowflake schema design, and entity-relationship modeling for both OLTP and OLAP workloads
• Version control and DevOps: Git, GitHub, pull request workflows, and CI/CD pipelines
• Data Visualization: Power BI, Tableau
• Strong analytical problem-solving -- able to decompose ambiguous business problems into clean technical solutions
• Clear written and verbal communication with both technical peers and non-technical stakeholders
• Self-directed with strong attention to detail; comfortable owning work end-to-end
• 5 to 8 years of hands-on data engineering experience in production environments
• Proven track record designing and delivering data platforms on Azure and/or AWS
• Demonstrated experience migrating or modernizing legacy on-premises data infrastructure to cloud-native solutions
• Hands-on experience running workloads with Azure Container Apps Jobs or a comparable containerized job execution platform
• Experience with MS Fabric in a production capacity, including Fabric Warehouses and OneLake integration
• Familiarity with dbt (data build tool) or similar transformation frameworks
• Exposure to streaming or near-real-time data ingestion patterns (Event Hub, Kafka, Kinesis)
• Experience with Workday, Adaptive Planning, or other ERP/FP&A source systems
• Power BI experience including semantic model development, dataset optimization, or DirectQuery/Import mode tradeoffs
• Agile/Scrum team experience; comfort working in iterative delivery cycles
• Relevant cloud certifications: Microsoft Azure Data Engineer (DP-203), AWS Certified Data Analytics, or equivalent
• Bachelor's degree in Computer Science, Information Systems, Data Science or a related field. In lieu of formal education, equivalent professional experience demonstrating the same depth of knowledge is accepted