wizeline20d ago

SR Data Analyst (Sigma)

Colombiasenior

Data ScienceData EngineeringData AnalystDataData & AI

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Quick Summary

Key Responsibilities

Design and build advanced Sigma workbooks using complex formulas, child elements, and dynamic filtering to support diverse global business units and functional domains.

Requirements Summary

Act as the Sigma Subject Matter Expert (SME), training other analysts and non-technical business users on how to explore data independently within the platform.

Technical Tools

Data ScienceData EngineeringData AnalystDataData & AI

Responsibilities

~1 min read

→Sigma Workbook Development: Design and build advanced Sigma workbooks using complex formulas, child elements, and dynamic filtering to support diverse global business units and functional domains.
→Data Modeling (Consumption Layer): Collaborate with Data Engineers to define the structure of reporting tables, ensuring models are optimized for Sigma’s query engine and live-connection architecture.
→Stakeholder Management: Work directly with business leadership and product owners to translate high-level business requirements into technical visualization specifications.
→Enablement: Act as the Sigma Subject Matter Expert (SME), training other analysts and non-technical business users on how to explore data independently within the platform.
→Observability & Performance: Monitor query performance and latency within the BI layer, optimizing workbooks to ensure a seamless user experience and efficient warehouse utilization.
→Security & Governance: Implement and maintain Row-Level Security (RLS) and Role-Based Access Control (RBAC) within Sigma workbooks, adhering to strict internal data governance policies for sensitive enterprise data.

5+ years of experience in Data Analytics or Business Intelligence.
2+ years of hands-on experience building complex workbooks with Sigma Computing. Deep understanding of Sigma’s specialized functions, Dataset/Workbook relationships, and Materialization features.
Proven track record of delivering executive-level dashboards and analytics products in a high-growth environment.
Strong communication skills; ability to explain technical data concepts to non-technical stakeholders and leadership.

AI Tooling Proficiency: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows.
Data Warehouse: Snowflake
Data Transformation: dbt Cloud
Cloud Infrastructure: AWS
Observability & Monitoring: Datadog