Senior Data Engineer
New
J
JobgetherIT Security
Based in United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Required Skills
- PythonSQLMicrosoft AzureMicrosoft Power BITerraformdbtDatabricksAzure DevOps
Requirements
- Significant professional experience delivering complex data engineering, cloud migration, data modernization, or related technology initiatives.
- Strong hands-on experience with Microsoft Azure, including services such as Azure Data Lake and Azure Synapse.
- Proven expertise with Databricks and modern cloud-based data engineering architectures.
- Strong knowledge of data warehousing methodologies, dimensional modeling, ETL processes, and scalable data architecture.
- Hands-on experience with dbt for developing and managing ETL and transformation workloads.
- Strong Python programming skills for data extraction, automation, API integrations, and engineering workflows.
- Experience working with REST APIs and integrating external data sources into cloud-based pipelines.
- Advanced Power BI experience, including semantic modeling, Power BI Fabric, SQL endpoints, lakehouse architectures, and Power BI Service.
- Experience migrating reporting environments from legacy on-premises SSRS solutions to modern cloud-based reporting platforms.
- Strong experience with Azure DevOps and CI/CD implementation for data engineering projects.
- Hands-on experience with Terraform for cloud infrastructure management is preferred.
- Experience working with outsourced vendors, contractors, and distributed internal teams.
- Excellent written and verbal English communication skills.
- Proven ability to work effectively within Agile development methodologies and two-week sprint cycles.
Responsibilities
- Lead the migration of 10–15 years of accumulated data from legacy SQL Server, SSRS, SSAS, and SAP Data Services environments to Microsoft Azure-based infrastructure.
- Design and implement scalable cloud data solutions using Azure Data Lake, Azure Synapse, Databricks, Power BI, and related technologies.
- Develop dimensional data models and data warehousing solutions using dbt, Python, SQL, and modern data engineering practices.
- Build and manage secure, reliable, and scalable ETL pipelines using dbt, Databricks notebooks, REST APIs, and other appropriate technologies.
- Modernize reporting capabilities by supporting the migration from on-premises SSRS to Power BI Service.
- Develop Power BI semantic models, SQL endpoints, lakehouse structures, and other reporting components within Microsoft Fabric.
- Establish robust reporting structures that improve data accessibility and enable actionable insights for global data stewards and other organizational teams.
- Lead data workflow modernization and implement CI/CD practices using Azure DevOps, Terraform, Python automation, and related tools.
- Collaborate closely with internal stakeholders, contractors, and outsourced vendors to coordinate technical delivery and ensure project objectives are met.
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