Key skills
Azure Data StackData EngineeringPythonDatabricksCI/CD PipelinesData GovernanceHigh-Scale Data IngestionAIETLELTData LakeAnalyticsSparkApache SparkAzureGitHub ActionsAzure DevOpsGitHubVersion ControlServiceNowSaaSSalesforceCI/CD
About this role
MSH is seeking an exceptional Staff Data Engineer to build the high performance foundation that powers the company’s internal business analytics. In this pivotal role, you will partner with a Staff Analytics Engineer to design and build the end-to-end delivery of the data ecosystem, ensuring timely, actionable insights for informed decision-making.
Responsibilities:
- Infrastructure Architecture: Design and implement the core architecture for the company’s data ecosystem that will be used for business analytics. This includes the end to-end architecture from the data in source systems to delivery in visualizations
- High-Scale Ingestion: Build robust Azure Data Factory pipelines to pull data from disparate source systems (Salesforce, ServiceNow, D365) to Azure data lake
- Standards & Governance: Set the technical standards for the Business Operations engineering team. You will define how the team handles CI/CD, version control, and data quality testing at the ingestion level
- System Reliability: Ensure the raw and bronze data layers are available and up-to-date, minimizing downtime
Requirements:
- 7+ years of progressive experience in Data Engineering, with a specific focus on designing and building cloud infrastructure and high-volume data movement
- Deep expertise in architecting the Azure Data Stack (Azure Data Factory, Azure Data Lake Storage, Databricks)
- Proven ability to build robust, scalable ELT/ETL pipelines using Azure Data Factory and Databricks
- Expert-level proficiency in Python and Apache Spark for distributed data processing
- Experience implementing enterprise-grade data governance, and data lineage
- Strong experience implementing CI/CD pipelines (Azure DevOps or GitHub Actions) for data infrastructure
- Experience leveraging LLMs and AI-assisted development tools to accelerate data engineering workflows, improve code quality, and automate repetitive technical tasks
- Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a closely related technical discipline
- Master's or equivalent in Computer Science, Engineering, or Cloud/Data Systems
- Prior experience working in a technology company or SaaS environment