Software Data Operations Engineer

About MAQ Software 

We exist to build great software. It’s our shared purpose and brand promise to our customers. As a Microsoft Fabric Featured Partner, MAQ Software enables leading companies to accelerate their data and AI initiatives.

We work with 25 Fortune 500 companies, emphasizing enterprise customers. As a premier supplier to Microsoft for two decades, our clients benefit from our extensive insights into the platform and engineering practices. Microsoft has awarded us eleven specializations for meeting their highest standards of service.

MAQ Software is strategically aligned with Microsoft Corporation and uses Microsoft technical stack. We are a Microsoft Fabric Featured Partner and many of our customer solutions use Microsoft Azure, Microsoft Fabric, and Microsoft copilots.

Our clients choose us for our commitment to consistent outcomes, reduced time to market, and a transparent workflow. They benefit from daily software updates, agile practices, domain expertise, and quickly implemented feedback.

With globally integrated teams in Plano, Texas, Redmond, Washington, NOIDA, Mumbai, and Hyderabad, India, we deliver solutions with increased velocity and tech intensity. Our dedication to customer success has led to sustained growth, recognized by Inc. magazine listing us on the Inc. 5000 list twelve 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 some of our projects: 

• Fintech Analytics Platform
  • Tools used: Azure Synapse, Data Factory, Databricks, Power BI
  • Challenges: Client needed a scalable analytics platform
  • Outcome: Enabled real-time analytics for scaling to 1000+ customers through our automated framework
  • Impact: reduced setup time and improved self-service analytic capabilities.
• Supermarket Power BI Migration
  • Tools used: Azure Synapse, Power BI
  • Outcome: Migrated the reporting stack to Power BI with backend integration to Azure Synapse, enabling direct queries for real-time insights.
  • Impact: Enhanced data accuracy, improved security, reduced operational costs, and empowered teams with automated reports and better decision-making.
• A US Western State Department of Security Chatbot
  • Tools used: Open AI and Web Interfaces
  • Challenge: Manual training for Program Service Evaluators (PSEs) was inefficient and consumed senior staff time.
  • Solution: Developed a chatbot trained on state policy manuals to answer evaluator questions and provide contextual support. The bot learned from feedback and automatically updated from policy documents.
  • Impact: Streamlined training, increased efficiency, and enabled PSEs to get accurate, real-time answers via an accessible conversational interface.
• Energy & Utilities IoT Data Analysis
  • Tools & Technologies: Azure Data Explorer (ADX), Power BI
  • Challenge: The client needed to process and analyze semi-structured IoT data (e.g., network logs) with frequent schema changes.
  • Solution: Built a pipeline to ingest, transform, and visualize JSON data using ADX and Power BI in DirectQuery mode.
  • Impact: Enabled real-time monitoring, reduced refresh time, and supported dynamic schema handling.
• Sales Forecasting Model for Multinational Food & Bev Chain
  • Tools & Technologies: Azure Databricks, Machine Learning
  • Challenge: The client wanted to improve the accuracy of its sales forecasts using historical and environmental data.
  • Solution: Built a hybrid ML model incorporating sales history, weather, and event data to predict demand and analyze seasonal trends.
  • Impact: Improved forecast accuracy (MAPE reduced from 0.13 to 0.09), identified lag patterns, and provided actionable insights to enhance strategic planning.

To read about some of our recent projects, visit https://maqsoftware.com/case-studies    

Responsibilities: 

Analyze existing systems (30%)    

• Collect requirement specifications to analyze business processes and determine the exact nature of user’s system requirements, map process flow, discuss with module leaders and core team members to decide on the architecture.  We use Microsoft Co-pilots including GitHub CoPilot.
• Analyze existing system structures to provide solutions to improve computer systems to use cloud-based systems and services using Copilots.
• Analyze user requirements to match data available to large computer database source systems to implement solutions at reasonable performance and cost.   
• Design the processing steps and propose new systems based on the user’s requirements. Interact with systems analysts/programmers to develop data migration tools, create processes for the new computer system and attend to ad-hoc issues related to day-to-day activities. Work with software developers in the implementation and testing phase.   

• Prepare software specifications, flow charts, and process diagrams for software programmers to follow. Develop and maintain 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%)    

• Interact with systems analysts/programmers to develop data migration tools, create processes for the new computer system and attend to ad-hoc issues related to day-to-day activities.    
• Work with other software developers in the implementation and testing phase.   
• Set up test environment 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, Data Science, Information Systems, Electrical Engineering, Applied Computational Math Sciences, or related Engineering discipline.