Senior Data Analyst (AWS & Quicksight) |8+ Years |Remote at TMS LLC

, Oregon, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Feb, 26

Salary

0.0

Posted On

25 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analytics, AWS, Quicksight, SQL, Data Validation, Data Visualization, Data Architecture, Data Quality, Documentation, Collaboration, KPI Definition, Performance Metrics, AI, Machine Learning, Troubleshooting, Self-Service Analytics

Industry

IT Services and IT Consulting

Description

Job Description Job Title: Senior Data Analyst (AWS & Quicksight) Location: Remote Duration: 6+ Months Overview: We’re seeking a highly skilled Senior Data Analyst to support analytics and reporting for our AI and Generative AI solutions team. This role is ideal for someone who is technically strong, detail-oriented, proactive, and thrives in a fast-paced environment where data quality, accuracy, and independence matter. You will be responsible for defining, validating, and delivering data requirements that enable the creation of usage and performance dashboards in Amazon Quicksight, using data stored across AWS Aurora, DynamoDB, and Athena. You should be comfortable navigating data architectures, identifying the right fields and tables, and collaborating with engineers to ensure end-to-end data integrity—without needing step-by-step direction. Responsibilities: Translate business and analytics needs into clear, structured requirements documents for Quicksight dashboards and reports. Independently identify source data tables, fields, and relationships across Aurora, DynamoDB, and Athena. Write, optimize, and validate queries to extract and transform data for analysis. Perform data validation and QA to ensure accuracy, completeness, and consistency across multiple data sources. Collaborate with product managers, engineers, and AI platform teams to define meaningful KPIs and metrics related to usage, adoption, and performance. Develop robust documentation and data dictionaries for reproducibility and handoff. Provide timely status updates, participate in daily standups, and meet project deadlines with minimal oversight. Contribute insights on data trends, patterns, and anomalies for continuous improvement of our AI/agentic systems reporting. Qualifications and Experience: 5+ years of hands-on data analytics experience, with demonstrated ability to work independently on data discovery and requirements definition. Experience creating compelling and easy-to-understand dashboards for data visualization. Expert-level SQL and experience querying AWS Aurora, DynamoDB, and Athena. Work with complex data models, including creating joins, foreign keys, and parent-child relationships in SQL databases. Collaborate with developers to request necessary database views or modifications to support custom reporting needs. Support business users through self-service analytics using AWS including user management and troubleshooting login and access issues. Proven experience designing or supporting dashboards in Amazon Quicksight (or similar BI tools). Strong understanding of data validation, QA, and troubleshooting techniques. Ability to interpret business goals into technical data requirements with precision. Excellent documentation and communication skills; able to provide crisp updates and proactive issue escalation. Experience working in AI, machine learning, or digital product analytics environments preferred. Comfortable working across time zones and managing multiple priorities under tight deadlines. Work Environment: Remote (must be available 9am–5pm Eastern Time) Contractor role (3–6 months with potential extension) Collaborative, agile, and high-performing AI product environment Thanks & Regards, Additional Information All your information will be kept confidential according to EEO guidelines.

Responsibilities

The Senior Data Analyst will define, validate, and deliver data requirements for usage and performance dashboards in Amazon Quicksight. They will collaborate with engineers and product managers to ensure data integrity and provide insights on data trends.