> Markdown version of [/jobs/ext/4695276-data-analytics](https://www.wearedevelopers.com/jobs/ext/4695276-data-analytics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analytics - **Company:** McDonald's - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $95,538 - $119,423 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Business Process Management, Information Systems, Data as a Services, Data Architecture, Data Validation, Data Discovery, Data Governance, Extract Transform Load (ETL), Data Warehousing, Database Queries, Power BI, Requirements Management, System Testing, Azure Data Factory, Snowflake, Kubernetes, Information Technology, Data Lineage, Data Analytics, Integration Frameworks, Data Pipelines - **Published:** November 12, 2026 - **Apply:** https://dejobs.org/x/x/C917E17DB39B4E11A64BEFF044AF3A44/job/ ## About the Role * Bachelor's degree in Data Analytics, Information Systems, Computer Science, Business, or related field. * 5+ years of experience in data analytics, business analysis, or related disciplines. * Demonstrated experience gathering and documenting business and technical requirements. * Strong SQL skills and experience querying large datasets. * Experience working with modern data warehouses and enterprise reporting platforms. * Understanding of data modeling concepts, business rules, and transformation logic. * Experience partnering with both business stakeholders and technical delivery teams. * Strong analytical, problem-solving, and communication skills. * Ability to translate technical concepts into business-friendly language and vice versa. Preferred * Experience with AWS, Snowflake Microsoft Azure or other data services. * Experience working with medallion architecture and lakehouse concepts. * Experience with data pipelines and orchestration platforms. * Experience with Power BI or similar business intelligence tools. * Familiarity with Azure Data Factory, Synapse, Fabric, or related platforms. * Experience working with third-party development partners or offshore delivery teams. * Experience supporting nonprofit or mission-driven organizations ## Description Business Engagement & Requirements Management * Partner with business stakeholders to understand reporting, analytics, and data needs. * Lead data discovery sessions, workshops, and data requirements gathering activities. * Translate business requirements into data requirements. * Document business processes, workflows, data definitions, and acceptance criteria. * Serve as the primary liaison between business stakeholders and technical development teams. * Facilitate prioritization discussions and support backlog management activities. Data Analysis & Analytics * Analyze complex datasets to identify trends, patterns, and actionable insights. * Develop and support reports, dashboards, scorecards, and self-service analytics solutions. * Perform data validation, reconciliation, and root cause analysis. * Define and document key performance indicators (KPIs) and business metrics. * Support users in interpreting data and applying insights to operational and strategic decisions. Data Architecture & Engineering Partnership * Collaborate with technical teams to design and implement scalable data solutions. * Work within modern data architectures, including medallion (Bronze, Silver, Gold) data frameworks. * Assist in defining source-to-target mappings and business transformation rules. * Partner with developers and engineers to design and validate data pipelines. * Understand and evaluate ETL/ELT processes, data lineage, and data quality controls. * Participate in the review and validation of transformation logic and business rules. Solution Delivery & Governance * Support end-to-end solution delivery from requirements through implementation. * Participate in system testing, user acceptance testing, and production validation. * Ensure delivered solutions meet business expectations and governance standards. * Promote data quality, consistency, and stewardship across the organization. * Contribute to data governance and documentation initiatives.