Senior BI Engineer

Working at Tech Holding isn't just a job, it's an opportunity to be a part of something bigger. We are a full-service consulting firm that was founded on the premise of delivering predictable outcomes and high-quality solutions to our clients. Our founders and team members have industry experience and have held senior positions in a wide variety of companies – from emerging startups to large Fortune 50 firms – and we have taken our combined experiences and developed a unique approach that is supported by the principles of deep expertise, integrity, transparency, and dependability.

About the Role

We are looking for a Senior BI Engineer to join our team and lead the analytics and reporting workstream of a large-scale AWS data platform modernization. You will be responsible for designing semantic data models, standardizing enterprise KPI definitions, building executive and self-service dashboards, migrating legacy Power BI workloads to Amazon QuickSight, and enabling natural language and AI-assisted analytics experiences.

The ideal candidate has deep expertise in Amazon QuickSight, dimensional data modeling, semantic layers, and BI storytelling, along with hands-on experience translating complex business requirements into trusted, governed, and scalable reporting solutions.

Key Responsibilities

• Design and build executive dashboards covering key business, operational, and performance metrics.
• Develop longitudinal cohort analysis and self-service analytics capabilities for business stakeholders.
• Build and optimize Amazon QuickSight semantic datasets, including SPICE capacity, refresh, and performance tuning.
• Migrate prioritized Power BI dashboards and reports to Amazon QuickSight.
• Partner with data engineering to define semantic layers, canonical data models, and standardized enterprise KPI definitions across multiple business units.
• Contribute to the enterprise business glossary, data dictionary, and KPI catalog, ensuring consistent business definitions across all reporting.
• Support natural language and conversational analytics experiences, enabling business users to query metrics in plain language.
• Configure knowledge repositories that leverage the business glossary, KPI catalog, and semantic definitions for AI-assisted data exploration.
• Conduct dashboard validation, user feedback sessions, and iterative refinement with business stakeholders.
• Establish reporting standards, row-level security, and governance for dashboards and datasets.
• Participate in UAT, production deployments, knowledge transfer, and post-production support.

Required Skills & Qualifications

• 5+ years of experience in Business Intelligence, analytics engineering, or a closely related field.
• Strong hands-on expertise with Amazon QuickSight (datasets, SPICE, calculated fields, parameters, RLS, dashboard design).
• Proven experience migrating from Power BI to QuickSight (or comparable BI-to-BI migrations).
• Strong SQL skills, including complex queries, window functions, and performance tuning.
• Solid understanding of dimensional data modeling, semantic layers, and star/snowflake schemas.
• Experience defining and standardizing enterprise KPIs, business glossaries, and data dictionaries.
• Working knowledge of the AWS analytics stack, including Amazon Redshift, Amazon Athena, and Amazon S3 as reporting sources.
• Experience building self-service analytics environments and enabling non-technical business users.
• Strong data storytelling and dashboard UX skills; ability to translate ambiguous business needs into clear, actionable visuals.
• Familiarity with Git, CI/CD, and version-controlled BI development practices.
• Excellent analytical, troubleshooting, stakeholder-management, and communication skills.

Preferred Qualifications

• Familiarity with Amazon Bedrock, natural language / conversational analytics, or LLM-assisted BI.
• Experience with Power BI (DAX, Power Query) for migration analysis.
• Knowledge of AWS Lake Formation, AWS Glue Data Catalog, and metadata/lineage tooling.
• Exposure to predictive analytics outputs and visualizing model results.
• AWS Certification (Data Engineer, Data Analytics Specialty, or Solutions Architect) is a plus.