Software Data Operations Engineer

Job Description

Job Description

Software Data Operations Engineer 
Plano (Dallas), Texas

About MAQ Software

MAQ Software enables leading companies to accelerate their business intelligence and analytics initiatives. Our AI-powered solutions enable clients to improve their productivity, reduce costs, increase sales, and build stronger customer relationships.

Our clients consistently recognize us for providing architecture and governance frameworks using the Well-Architected Framework, implementing best practices to optimize reports, and building team capability through training programs.

Clients choose to work with us because they are confident in our software delivery. Our confidence results from a commitment to consistent outcomes, reduced time to market, and a transparent workflow. Clients benefit from daily software updates, agile practices, domain expertise, AI adoption, and rapid feedback implementation.

As a premier supplier to Microsoft for over two decades, MAQ Software clients gain extensive insights and engineering practices across the Microsoft platform and can improve their implementations with our breadth and depth of expertise.

As one of the top 25 global partners, Microsoft has awarded MAQ Software eight specializations for meeting their highest standards of service delivery to Fortune 500 companies.

With over 1,800 engineers, MAQ Software has globally integrated teams in Redmond, Washington; Plano, Texas; and Noida, Mumbai, and Hyderabad, India, delivering solutions with increased velocity and tech intensity. Our daily delivery and feedback model offers the flexibility to adapt solutions to changing business needs.

MAQ Software’s dedication to customer success has led to sustained growth. Inc. magazine has recognized MAQ Software for sustained organic growth by listing us on the Inc. 5000 list thirteen times —a rare honor.

Engineering culture

At MAQ Software, we foster a strong engineering culture with a can-do attitude. Our key managers come from excellent educational backgrounds and have significant experience in growing a company and mentoring software engineers. Due to our smaller size, we are agile and able to adopt the latest technologies and computing trends ahead of larger industry players.

As a part of our globally distributed engineering team, our engineers gain exposure to the latest software engineering practices and fast development cycles, providing them with the opportunity to work on challenging technical problems that utilize cutting-edge technologies for fast-paced software delivery. Our collaborative and supportive work environment encourages innovation and growth, making our company an exciting and rewarding place to work.

Examples of our projects:

• We built an agentic AI solution that redefined event information access for a global technology leader, delivering instant, accurate answers to attendee questions at scale. Using Azure OpenAI Service, Azure AI Search, and Azure Machine Learning, combined with Retrieval-Augmented Generation (RAG), we engineered a secure, multilingual Copilot platform capable of processing data from 22 file formats across multiple sources. Our team leveraged Azure Databricks for advanced data transformation, Azure Front Door for global load balancing, and Microsoft Entra ID with Azure Key Vault for enterprise-grade security. The result: a system that served over 200,000 users, handled millions of interactions, and reduced support requests by 70%, setting a new benchmark for scalable, intelligent, and personalized event experiences.

• We built a high-performance reporting solution that redefined data refresh efficiency for a leading office supply retailer, delivering near real-time insights and dramatically faster report access. By integrating Snowflake-managed Iceberg tables into Microsoft Fabric via OneLake shortcuts and leveraging Power BI’s Direct Lake mode, we built a scalable architecture that eliminated data duplication and significantly reduced latency. Our team leveraged Azure Data Lake Storage for external volume dumps, semantic modeling for streamlined analytics, and Fabric F256 SKU with autoscale for optimized compute. The result: report load times dropped by 80%, refresh cycles shrank from 10 days to minutes, and infrastructure costs fell by 60%, setting a new benchmark for enterprise-grade reporting performance.

• We helped a global industrial technology leader transform its construction operations by replacing a fragmented, batch-based ERP system with a real-time intelligence solution built on Microsoft Fabric. The previous setup—based on Databricks and Snowflake—struggled with delayed data updates, high maintenance, and siloed systems. By implementing Microsoft Fabric’s Real-Time Intelligence capabilities, including Eventstreams, Reflex, and Power BI dashboards, we enabled real-time data ingestion, anomaly detection, and instant insights. The result: 20–30% cost savings, 50% less IT maintenance, and a 10x improvement in data latency. This empowered faster decision-making, proactive issue resolution, and a more agile, data-driven organization.

• We helped a Fortune 500 office supply retailer modernize its reporting by migrating from MicroStrategy to Power BI. The legacy system was costly and inefficient, requiring over 150 duplicate reports and individual licenses for each user. Our solution consolidated these into just five dynamic Power BI reports, each customizable with bookmarks and filters. By leveraging Snowflake and Import Mode, we delivered a scalable semantic model and a user-friendly experience. The result: reduced license costs, faster reporting, and empowered business users with self-service analytics.

• We built an AI-powered chatbot for a global manufacturer of industrial test and diagnostic equipment to improve access to project lifecycle management data. Using Azure OpenAI, Azure AI Search, and Azure App Service, the solution indexed documents from SharePoint—including PDFs, Excel files, and dynamic web pages—into a centralized, searchable interface. Power Automate and custom code streamlined data ingestion and processing, while Azure Cosmos DB stored historical interactions. The chatbot enabled employees to retrieve accurate insights quickly, reducing manual effort and improving decision-making. Post-deployment, the client achieved higher productivity, lower operational costs, and seamless access to project data through a single unified interface.

To read about some of our recent projects, visit -studies

Responsibilities Analyze existing systems (30%)

• Collect requirement specifications to analyze business processes and determine the exact nature of user’s system requirements. Use tools like Microsoft 365 Copilot to summarize stakeholder input and map process flow from documents, emails, and meetings. Collaborate with module leaders and core team members to decide on system architecture.
• Analyze existing system structures to identify opportunities for migration to cloud-based platforms. Use GitHub Copilot to assist in refactoring legacy code and Microsoft Azure AI services to evaluate cloud readiness and performance benchmarks.
• Analyze user requirements and align them with available enterprise data sources to design solutions that deliver reliable performance and reasonable cost. Use tools such as GitHub Copilot to assist with query optimization and Azure DevOps MCP Server to validate data lineage and dependencies within project repositories.
• Design processing steps and recommend system solutions based on user requirements, ensuring clarity and scalability.

Develop specifications and workflow (25%)

• Prepare software specifications, flow charts, and process diagrams for software programmers to follow. Use GitHub Copilot to generate code templates and automate systems documentation such as design specifications, user manuals, technical manuals, descriptions of application operations, and methodology documentation.
• Analyze feasibility using commercially available software systems (e.g., Microsoft Azure versus Amazon Web Services) and reporting systems (e.g., Power BI versus Tableau).

Analyze and verify implementation (25%)

• Collaborate with systems analysts and programmers to develop data migration tools and define operational workflows for new systems.
• Work with software developers to use GitHub Copilot for accelerating code development.
• Set up the test environment, use GitHub Copilot to generate test cases, and use Playwright MCP to automate testing and compare data from multiple sources to verify reports for end users.

Review implementation status and reporting (10%)

• Participate in technical collaboration meetings and periodical reviews of implementation status.
• Report weekly task plan to the project management team for implementation of custom software.

Training and certifications (10%)

• Participate in technical training and complete relevant industry courses and certifications.

Qualifications

Undergraduate or graduate degree in Computer Science, Information Systems, Applied Computational Math Sciences, or related engineering discipline.

Benefits

• Annual salary range depends on education and experience.
• Comprehensive medical, dental and vision insurance with employee premiums paid in full. 
• 401(k) retirement plan with 3% company match and immediate vesting  
• Paid time off (three weeks)