Senior Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Date Engineer based in United States.

This is a senior-level opportunity to modernize a large and complex data environment by moving long-standing meeting house data from legacy systems into scalable cloud infrastructure. You will play a central role in migrating and transforming years of accumulated data while improving its consistency, security, accessibility, and global availability. The role combines cloud data engineering, data warehousing, ETL development, reporting, automation, and DevOps practices. You will work extensively with Microsoft Azure, Databricks, Power BI, dbt, Python, and modern data architecture patterns to build reliable and maintainable solutions. You will collaborate with internal teams and external vendors, helping ensure successful delivery while supporting knowledge transfer and continuous modernization. The position also provides an opportunity to influence reporting and analytics capabilities used across multiple departments and global data stewardship functions. This role is well suited to an experienced data engineer who can independently navigate complex migrations, make sound technical decisions, and deliver effectively in an Agile environment.

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Accountabilities

• 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.

• Support knowledge transfer by documenting solutions, communicating technical decisions, and helping internal teams adopt modern data technologies.

• Participate actively in Agile and sprint planning processes, contributing to two-week sprint cycles, making realistic commitments, and delivering agreed outcomes.

• Troubleshoot data pipelines, integrations, reporting workflows, and cloud infrastructure to maintain reliable operations.

• Identify opportunities to improve automation, scalability, security, data quality, and overall engineering efficiency.

• Evaluate and incorporate emerging data and machine learning technologies when they can improve document processing, reporting, or data workflows.

• Communicate technical concepts, project progress, risks, and dependencies clearly with both technical and non-technical stakeholders.

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, particularly in technical and project environments.

• Proven ability to work effectively within Agile development methodologies and two-week sprint cycles.

• Strong problem-solving, analytical, organizational, and prioritization skills.

• Ability to operate independently, make sound technical decisions, and deliver complex projects without extensive onboarding or ongoing guidance.

• Familiarity with machine learning-based document processing technologies is a plus.

Benefits

• Fully remote working environment.

• Opportunity to work on a major cloud data modernization and migration initiative.

• Exposure to Microsoft Azure, Databricks, Power BI Fabric, dbt, Python, Terraform, and modern DevOps practices.

• Opportunity to modernize legacy reporting and data infrastructure at meaningful organizational scale.

• Collaboration with cross-functional teams, technical specialists, and external technology partners across multiple regions.

• Opportunity to influence enterprise data accessibility, reporting, automation, and analytics capabilities.

• Agile working environment with structured sprint cycles and clear delivery ownership.

• Opportunity to contribute to emerging applications of automation and machine learning within data workflows.

• Supportive and collaborative environment focused on continuous learning and innovation.

• Significant technical ownership and autonomy within a senior engineering role.

\nHow Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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