Major Responsibilities: Core Analytics & Data Engineering: Design, build, and maintain analytics-ready datasets and data models to support reporting, dashboards, and advanced analytics. Develop and optimize data transformation logic to ensure performant and reliable analytical outputs. Support the creation of curated analytics layers that enable consistent and reusable insights across teams. Troubleshoot and resolve data quality, performance, and pipeline issues impacting analytics delivery. Analytics & Reporting Enablement: Partner with business and technical stakeholders to translate analytical requirements into datasets, metrics, and visualizations. Enable downstream consumption of analytics outputs through reporting tools and dashboards. Support ad-hoc analysis and exploratory data needs as required. Power Platform Enablement (Secondary Scope): Enable and support analytics-driven solutions built using Power BI, Power Apps, and Power Automate. Design and maintain data integrations that allow Power Platform solutions to consume analytics datasets efficiently. Collaborate with Power Platform developers to ensure analytics outputs are structured and optimized for application and automation use cases. Assist in troubleshooting data-related issues impacting Power Platform apps, flows, and reports. Collaboration & Continuous Improvement: Work closely with cross-functional teams to improve analytics workflows and delivery processes. Contribute to continuous improvement of analytics practices, performance, and usability. Document analytics solutions, datasets, and integration patterns to support maintainability and knowledge sharing. Write and maintain SQL-based data transformations and automated data quality tests to ensure data integrity. Mentor junior team members and contribute to team knowledge development and technical growth. Job Requirements: Education: Bachelor’s degree in Computer Science, Data Science, Information Systems, Statistics, or a related STEM field; or an equivalent combination of education, certifications, and professional experience. 3–5 years of experience in data analytics engineering, analytics development, or related roles supporting enterprise analytics solutions. Advanced SQL proficiency, including CTEs, window functions, complex joins, and query performance optimization. Proficiency in Python for data manipulation, pipeline scripting, and automation tasks. Experience with Git version control for collaborative development and code management. Experience designing and maintaining ETL/ELT pipelines and data warehouse solutions. Strong understanding of data warehousing concepts, dimensional modeling, and star/snowflake schema design. Hands-on experience working with Power BI and integrating analytics datasets into Power Apps and Power Automate solutions. Strong understanding of data modeling, analytical datasets, and how analytics outputs are consumed by reporting tools and applications. Familiarity with Microsoft 365 and Azure Entra ID for secure access to analytics and Power Platform solutions. Experience collaborating with Power Platform developers to support analytics-driven apps, reports, and automations. Strong communication and teamwork skills, with the ability to explain analytical concepts to non-technical audiences. Experience supporting business users and analysts by enabling self-service analytics and data-driven innovation. Certifications such as (preferred but not required): Microsoft Certified: Power BI Data Analyst Associate, Microsoft Certified: Azure Data Engineer Associate, Microsoft Certified: Power Platform Functional Consultant Associate, dbt Analytics Engineering Certification. Language Skills: Professional working proficiency in English (written and spoken). Preferred experience & skills: Advanced experience designing and optimizing Power BI datasets and enterprise reporting models, Experience integrating analytics outputs into Power Apps and Power Automate solutions, Working knowledge of Azure data services and cloud-based analytics platforms, Experience implementing data security, access controls, and governance best practices, Familiarity with DevOps or structured release management for analytics solutions, Ability to translate business needs into scalable analytics designs, Ability to balance technical depth with user-centered solution design, Ability to collaborate across technical and non-technical teams, Ability to influence decisions through data and structured reasoning, Ability to prioritize competing demands in fast-moving environments, Ability to simplify complex analytical concepts for diverse audiences, Ability to continuously improve analytics processes and standards, Strong ownership mindset and accountability for solution outcomes, Experience with dbt (data build tool) or similar SQL-based transformation frameworks, Experience implementing automated data quality testing and validation frameworks, Familiarity with data pipeline orchestration tools (e.g., Apache Airflow, Dagster), Familiarity with machine learning concepts and AI-assisted data workflows.
