Senior Business Intelligence Engineer, Cint

• Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, Statistics, or a related quantitative field
• Experience: 5+ years of experience in BI engineering, data engineering, or a highly technical analytics role
• Data Integration & Architecture: Practical experience working with data from multiple, disparate systems and successfully aligning them into unified, high-integrity data models within a modern data warehouse
• Data Warehousing: Deep practical experience in data warehousing principles, proven experience working with cloud data warehouses such as Databricks, Snowflake or BigQuery
• Preferably Databricks
• Data Modeling: Strong understanding of dimensional modeling (Star/Snowflake schemas) and modern data stack tools (e.g., dbt)
• SQL Mastery: Expert-level SQL skills (complex joins, window functions, and performance tuning)
• BI Tooling: Deep expertise in at least one enterprise BI platform (e.g. Tableau, Power BI, Looker, or Sigma)
• Preferably Omni + Power BI
• Strategic Solutioning & Communication: Proven analytical and creative design skills, with the ability to translate complex problem-solving and system designs into clear narratives for audiences ranging from entry-level employees to senior leadership
• Collaborative Agility: Ability to thrive in a team-oriented, fast-paced environment while managing multiple concurrent projects and shifting priorities seamlessly as business needs evolve

Desirable

• Pipeline & Data Modeling: Design, build, and maintain scalable automated data pipelines (ETL/ELT) and data models that support complex analytical requirements
• Strategic Visualization: Develop sophisticated dashboards and reporting tools that provide "at-a-glance" insights for executive leadership and deep-dive capabilities for analysts
• Data Governance: Establish and enforce best practices for data documentation, metadata management, and data quality assurance to ensure "one source of the truth."
• Performance Optimization: Audit and optimize SQL queries and dashboard performance to ensure low-latency access to large datasets
• Stakeholder Partnership: Act as a technical consultant to non-technical departments, helping them define Key Performance Indicators (KPIs) and translate business questions into technical requirements
• Mentorship: Lead code reviews and mentor junior engineers on data modeling techniques and visualization best practices