Senior Analytics Engineer II - R01564337

About Brillio:

Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.

Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.

Analytics Engineer

• The Senior Analytics Engineer plays a pivotal role in enabling a data driven culture by designing, building, and scaling high quality analytics infrastructure. This role sits at the intersection of data engineering, analytics, and business intelligence—transforming raw data into trusted, actionable insights that drive strategic and operational decision making across the organization.
  As a senior member of the Data & Analytics team, you will own end to end delivery of analytical solutions, partner closely with business stakeholders, and apply strong engineering rigor to ensure scalability, reliability, and self service capabilities across the analytics platform.
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• Key Responsibilities
  •    Architect the Business Insights Foundation 
  o    Partner with data engineers to design, build, and maintain analytics transformation layers that act as a single source of truth for downstream reporting, BI, and data science use cases.
  •    Deliver Business Facing Insights 
  o    Own the complete analytics lifecycle—from requirements gathering and data modeling to scalable dashboards and self service analytics solutions.
  •    Stakeholder Collaboration 
  o    Serve as the technical analytics partner to business stakeholders, translating functional and strategic needs into automated, scalable data solutions.
  •    Data Storytelling 
  o    Develop compelling dashboards, metrics, and analytical narratives that communicate insights effectively to both technical and non technical audiences.
  •    Build for Scale & Reusability 
  o    Design standardized, reusable business metrics and data models that support automated reporting and enable deep dive self service analysis.
  •    Apply Engineering Best Practices 
  o    Improve analytics infrastructure using software engineering principles such as version control, modular design, testing, documentation, and performance optimization.
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• Required Skills & Experience
  •    Experience 
  o    4+ years of industry experience in analytics engineering, data engineering, or advanced analytics roles.
  •    SQL & Data Modeling 
  o    Expert level SQL skills with demonstrated experience building production grade data models in cloud data lakehouse environments such as Snowflake or Databricks.
  •    Analytics Platform Expertise 
  o    Strong experience designing scalable analytics layers that support BI, operational reporting, and advanced analysis.
  •    Visualization & Self Service Analytics 
  o    Hands on experience developing dashboards and self service analytics using tools such as Tableau, Power BI, or Looker.
  •    Business Acumen 
  o    Proven ability to partner with business users and translate ambiguous requirements into impactful analytics solutions.
  •    Ownership Mentality 
  o    Self starter with strong accountability, a growth mindset, and the ability to deliver high quality outcomes independently and collaboratively.
  •    Collaboration 
  o    Team oriented mindset with excellent communication skills and appreciation for diverse perspectives.
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• Nice to Have Skills
  •    Experience with customer acquisition, sales funnel, or revenue analytics.
  •    Prior exposure to the real estate industry or other fast moving, market driven domains.
  •    Familiarity with metrics governance, data quality frameworks, or analytics enablement practices.
  •    Experience working closely with data science or experimentation teams.

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