Sigma Dashboard Developer

• Title:- Sigma Dashboard Developer
• Location: Jersey City, NJ or Wilmington, DE or New York City, NY (5 Days office) there will be 2 rounds of client interviews (Virtually)
• Overall – 8 years
• Vertical- Banking

JD-

The Sigma Dashboard Developer will design, build, and maintain enterprise-grade dashboards and analytical solutions using Sigma Computing. This is not a visualization-only role. The candidate must be comfortable working deep in the data layer, including understanding and building data models in Databricks, writing SQL against Delta tables and lakehouse architectures, and ensuring the analytical layer is performant, accurate, and well-structured.

The candidate will partner closely with business stakeholders, data engineers, and analytics leads to translate complex business requirements into intuitive, reliable, and scalable dashboard solutions. They will be expected to operate independently, move quickly, and deliver with a high degree of technical rigor.

Required Skills & Qualifications

• Hands-on, production experience with Sigma Computing, including workbook development, input tables, data exploration, and publishing for end-user consumption.
• Strong SQL skills with demonstrated experience writing complex queries against large-scale data platforms, including joins, window functions, CTEs, and aggregations.
• Direct experience working with Databricks, including querying Delta tables, understanding lakehouse architecture, and navigating Unity Catalog or equivalent data governance structures.
• Solid data modeling background, with the ability to design and build analytical models including facts, dimensions, and summary layers that are performant and business-aligned.
• Proven ability to translate ambiguous business requirements into structured, accurate, and scalable dashboard solutions.
• Experience with BI tools and semantic layers beyond Sigma, demonstrating breadth of analytical platform understanding and transferable technical knowledge.
• Strong understanding of data concepts including grain, lineage, slowly changing dimensions, and aggregation patterns.
• Ability to work independently in a fast-paced contractor capacity with minimal oversight and high delivery accountability.

Core Competencies

• Advanced Sigma Computing dashboard development and workbook design.
• Data modeling and analytics engineering within Databricks and lakehouse environments.
• SQL development at enterprise scale with attention to performance and accuracy.
• Business requirements translation into technical dashboard specifications.
• Semantic layer design and metric standardization.
• Data validation, reconciliation, and documentation discipline.

Preferred / Nice-to-Have Skills

• Experience in financial services, wealth management, or similarly complex, regulated data environments with sensitive or multi-domain data.
• Familiarity with dbt or similar analytics engineering frameworks for model documentation and transformation layer management.
• Exposure to data governance practices including column-level security, row-level access control, and audit logging at the dashboard and data platform level.
• Experience working with cross-functional data teams including data engineers, data scientists, and product owners in an agile delivery model.
• Familiarity with Python or PySpark for lightweight data exploration or pipeline validation support.

Key Responsibilities

• Design, develop, and publish production-grade dashboards and workbooks in Sigma Computing, meeting business requirements for accuracy, usability, and performance.
• Understand, navigate, and contribute to data models in Databricks, including querying Delta tables, working within lakehouse architectures, and writing well-structured, optimized SQL.
• Build or refine data models and semantic layers that underpin dashboard development, including defining metrics, dimensions, aggregations, and business logic at the appropriate layer.
• Translate business requirements gathered from senior stakeholders and business analysts into dashboard designs that are intuitive, self-service ready, and aligned to how decisions are actually made.
• Validate data accuracy and reconcile dashboard outputs against source systems and upstream data pipelines, escalating discrepancies with clear documentation.
• Collaborate with data engineering teams to understand pipeline architecture, data availability, grain, and lineage, and to influence upstream data structures where dashboard requirements demand it.
• Document data models, dashboard logic, metric definitions, and design decisions to support maintainability, onboarding, and audit readiness.
• Optimize queries and workbook performance to ensure dashboards are responsive at enterprise data volumes.
• Support user acceptance testing and iterate on dashboard design based on structured stakeholder feedback.
• Participate in technical reviews and contribute to standards for dashboard development practices, naming conventions, and reusable components.