Sr. Azure Data Engineer - Databricks

Job Description

Job Description

Through NRI Resource Management Services (RMS), we offer custom talent solutions to help our clients meet their evolving technology and business needs. We help effectively match the right technology professional to their organization, recruiting for contract, contract-to-hire, and direct roles. Our client in Charlotte, NC has an immediate need for a Sr. Data Engineer. Please note that this is a contract to hire opportunity with our client and NOT with NRI.

Job Description: Senior Data Engineer

The Senior Data Engineer / Data Platform Engineer will take ownership of the architecture, infrastructure, and operational maturity of our data environment. This role is ideal for someone who thrives in a Medallion Architecture based Python DLT/ DBT environment hosted in Azure, enjoys maturing foundational systems, and is comfortable operating at the intersection of engineering, operations, and business stakeholders. The candidate must have exceptional communication skills, with ability to interact with key business stakeholders in delivering critical reporting & other data insights.

Key Responsibilities

Data Architecture & Platform Ownership

• Own the end-to-end architecture and infrastructure of the Azure-based data platform
• Design and implement a modern Lakehouse architecture to support analytics and reporting
• Establish best practices for data engineering, reliability, and operational excellence

Data Ingestion & Pipelines

• Design, build, and maintain API-driven and batch data pipelines
• Ingest data from multiple source systems across acquired entities
• Orchestrate workflows using Dagster
• Ensure pipelines are scalable, resilient, and well-monitored

Data Transformation & Analytics Enablement

• Transform raw, disparate data into clean, trusted, analytics-ready datasets
• Model data for consumption in Power BI (PBI)
• Partner with finance and business teams to align data structures with reporting needs

Operations & Troubleshooting

• Own data platform operations , including monitoring, alerting, and incident response
• Troubleshoot complex data and pipeline issues across ingestion, transformation, and reporting layers
• Continuously improve performance, reliability, and cost efficiency

Stakeholder Collaboration

• Work closely with the CFO and other senior stakeholders to understand reporting and analytics requirements
• Translate business needs into technical solutions
• Act as a trusted data engineering partner across the organization

Qualifications and Skills

Education and Experience

• Bachelor's degree in information systems, informatics, data science or a related field
• 5+ years of experience in data engineering, data platform engineering, or data operations
• Certifications including Microsoft Azure Data Engineer Associate , Databricks Certified Data Engineer, Python Institute Certifications (PCAP, PCPP) or DataCamp Certifications are highly desirable

Technical Knowledge

• Strong experience in Microsoft Azure data services (greenfield experience strongly preferred)
• Hands-on expertise with:
• Python (including DLT and DBT)
• Azure Data Bricks
• APIs, data pipelines, and ingestion frameworks
• Workflow orchestration (Dagster or similar tools)
• Experience building and operating Medallion Architected environments

· Strong experience supporting Power BI or similar BI tools

· Experience using GitHub or similar version control tools

Leadership and Communication

• Collaborate with the CFO and other senior stakeholders to understand reporting and analytics requirements, then accurately translate business needs into technical solutions
• Act as a trusted data engineering partner across the organization
• Communicate health and status of environment to leadership regularly

Problem-Solving and Decision-Making

• Excellent troubleshooting and problem-solving skills across data pipelines and platforms
• Influence prioritization of work to minimize technical debt and maintain performance

· Ability to work at a detailed level while maintaining the ‘big picture’ of the overall business vision

Key Performance Indicators

To measure the success the Senior Data Engineer is responsible for the following KPIs:

• Cloud and PaaS resource utilization in Data Environment
• Compliance with IT Data Security and IT general controls
• Time to fix pipeline failures and data environment defects and outages
• Increase usage of published PowerBI Reports