BI Engineer (Contract)

BI Engineer (Contract)

BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) BI Engineer (Contract) 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. Location: Remote Experience Required: 5+ Years Employment Type: Contract

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.

Tech Holding is hiring for this role on CareerPlace.

Apply on the company website through Tech Holding.

Imported from employer careers page. Source ref: 77601f80ba17.