Analytics Analyst - Quality

As part of the operational arm of data analytics, the Analytics Analyst - Quality will support the implementation of data governance decisions, maintain data quality documentation, and train end users on analytics solutions. The role involves developing and maintaining low-code applications, integrating data sources, and facilitating data governance processes to ensure the delivery of high-quality insights for business decision-making.

Key Responsibilities:

• Develop & Maintain Low-Code Applications: Design, develop, and enhance low-code applications using Mendix/Power Apps based on business requirements.
• Integrate with Data Sources: Connect applications to SQL databases, APIs, and other data sources for seamless data flow and business logic implementation.
• UI/UX Implementation: Create intuitive, responsive, and user-friendly interfaces ensuring a smooth end-user experience.
• Power BI Integration and Development: Embed Power BI dashboards within applications for real-time reporting and analytics.
• Performance Optimization: Write efficient queries and optimize application performance for scalability and security.
• Troubleshooting & Debugging: Identify, diagnose, and resolve technical issues in applications and ensure smooth deployment.
• Collaboration & Documentation: Work closely with business analysts, stakeholders, and cross-functional teams to gather requirements, document solutions, and provide technical guidance.
• Support Data Governance Processes: Facilitate intake processes to reduce rework and promote reuse of analytics solutions.
• Data Integration and Cleansing: Collaborate with peers to integrate data from warehouses, data lakes, and other source systems. Cleanse data to ensure report accuracy and reduce duplication, maintaining documentation of the cleansing process.
• Support Analytics Projects: Produce insights to improve business decision-making and deliver results using reports, business intelligence technology, or other appropriate mechanisms.
• Enforce Data Standards: Assist in establishing and enforcing guidelines and standards for data collection, integration, and processes.
• Data Ingestion: Support project work to ingest key data into the data lake, ensuring the creation and maintenance of relevant metadata and data profiles.
• Stakeholder Support: Assist stakeholders and business teams with finding necessary and relevant data.
• Promote Analytics Best Practices: Participate in relevant communities of practice and coach business users in developing capabilities within the analytics ecosystem.
• Communication Preparation: Assist with the preparation of communications to leaders and stakeholders.

Qualifications:

• Education: B. Tech in Computer Science (CS), Electrical & Electronics Engineering (EEE), Information Technology (IT), or a related field.
• Experience: Minimum 3 to 4 years of hands-on experience in Mendix/Power Apps, Power BI, and SQL.

Key Skills:

• Mendix/Power Apps
• Power BI
• SQL
• Power Automate
• GITLAB/GITHUB

Competencies:

• Collaborates: Building partnerships and working collaboratively with others to meet shared objectives.
• Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
• Customer Focus: Building strong customer relationships and delivering customer-centric solutions.
• Interpersonal Savvy: Relating openly and comfortably with diverse groups of people.
• Data Analytics: Discovering, interpreting, and communicating qualitative and quantitative data to extract meaningful patterns and business insights.
• Data Mining: Identifying relationships and patterns through data exploration and visualization techniques.
• Data Modeling: Creating, writing, and testing data models to meet business, technical, and compliance requirements.
• Data Communication and Visualization: Illustrating data visually to construct a narrative around business problems and solutions.
• Data Literacy: Expressing data in context and describing the use-case application and resulting value.
• Data Profiling: Assessing data issues and cleansing requirements to establish high-quality data.
• Data Quality: Identifying and correcting flaws in data to support effective information governance and decision-making.
• Values Differences: Recognizing the value that different perspectives and cultures bring to an organization.