We are looking for an experienced Analytics Engineer – Senior Associate to design, develop, and enhance scalable analytics and reporting solutions. The role will focus on transforming complex data into reliable, business-ready datasets, dashboards, and actionable insights using Amazon QuickSight, SQL, AWS data services, and modern analytics technologies. The ideal candidate will have strong hands-on analytics engineering skills, experience building executive and operational dashboards, and exposure to AI/Generative AI capabilities that can improve analytics, automation, and data-driven decision-making.

Key Responsibilities
• Design and develop interactive dashboards, reports, KPIs, and visualizations using Amazon QuickSight.
• Build scalable analytical datasets and semantic/data models to support reporting and self-service analytics.
• Develop complex SQL queries for data extraction, transformation, validation, and analysis.
• Work with AWS data platforms and services such as Amazon Redshift, S3, Athena, Glue, and QuickSight.
• Optimize dashboard performance, queries, datasets, and underlying data models.
• Translate business requirements into meaningful KPIs, metrics, dashboards, and analytical solutions.
• Perform data profiling, reconciliation, validation, and root-cause analysis to ensure data accuracy.
• Partner with Data Engineering, Product, Business, and Platform teams to deliver end-to-end analytics solutions.
• Support automation of recurring analytics/reporting processes.
• Apply appropriate access controls and data security practices for dashboards and datasets.
• Explore and implement AI/Generative AI-assisted analytics use cases, such as natural-language insights, automated summarization, anomaly identification, and intelligent reporting.




• Troubleshoot production analytics issues and continuously improve reporting performance and user experience.
• Document data definitions, business rules, KPIs, and reporting logic. Required Technical Skills Core Skills
• Strong Amazon QuickSight experience, including dashboards, datasets, calculated fields, filters, parameters, and visualization design.
• Advanced SQL and strong understanding of relational/data warehouse concepts.
• Experience with Amazon Redshift or comparable cloud data warehouses.
• Strong knowledge of data modeling, dimensional modeling, KPIs, metrics, and reporting design.
• Experience handling large datasets and optimizing analytical queries.
• Strong analytical, troubleshooting, and data-validation skills. AWS / Data
• Amazon QuickSight
• Amazon Redshift
• Amazon S3
• Amazon Athena
• AWS Glue
• IAM/security fundamentals
• ETL/ELT concepts Additional Analytics Skills
• Experience with Tableau and/or Power BI is desirable.
• Python/Pandas knowledge for analytics and automation is preferred.
• Understanding of APIs, JSON, CSV, Parquet, and common data integration patterns.
• Familiarity with Git and CI/CD practices is an advantage. AI / Generative AI Exposure Candidates should have working knowledge or practical exposure to areas such as:
• Generative AI and LLM-based analytics
• Natural-language querying and insight generation
• AI-assisted dashboard/report summarization
• Data classification and automated analytics workflows




• Prompt engineering fundamentals
• RAG (Retrieval-Augmented Generation) concepts
• Exposure to AWS AI services such as Amazon Bedrock is a plus
• Python-based integration with AI/ML services is desirable AI expertise is not expected to be the primary specialization, but the candidate should be comfortable adopting AI capabilities within modern analytics solutions. Experience & Qualifications
• Typically 4–7+ years of experience across analytics, BI, data engineering, or related areas.
• Strong hands-on experience delivering production-grade dashboards and analytical solutions.
• Experience working in an AWS-based data ecosystem.
• Ability to independently understand requirements and convert them into technical analytics solutions.
• Solid communication skills with the ability to work with technical teams and business stakeholders.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data/Analytics, or a related field, or equivalent practical experience. Preferred Profile An ideal candidate would have a skill mix roughly centered around: QuickSight + SQL + Data Modeling + AWS/Redshift + BI/Visualization + Python/Automation + AI/GenAI exposure This keeps the role firmly Analytics Engineering focused, while adding enough AWS and AI capability to make it suitable for a modern analytics organization.

We offer
you a competitive total rewards package, continuing education & training, and tremendous potential with a growing worldwide organization. DISCLAIMER: Nothing in this

job description
restricts management's right to assign or reassign duties and responsibilities of this job to other entities; including but not limited to subsidiaries, partners, or purchasers of Alight business units. .

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