Data Driven Decision Maker

1 day ago

Kota, Rajasthan, India beBeeAnalytics Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Lead Analytics Engineers drive business growth through data-driven insights. This pivotal role designs and scales analytics systems, fostering a future-ready ecosystem.

Key Responsibilities

  • 1. Data Architecture
    • Design datamarts and curated data views across domains.
    • Establish data modeling best practices, documentation, and governance.
    • Mentor team members on SQL and data engineering patterns.
  • 2. Dashboarding & Visualization
    • Develop dashboard standards, governance, and usability.
    • Design executive-level and operational dashboards.
    • Manage a backlog of dashboard requests with clear SLAs.
  • 3. Business Rule Engines
    • Own the design and governance of production rule engines for credit/fraud policies.
    • Ensure scalable, tested, and version-controlled deployment of rules.
    • Partner with Risk/Policy/Product teams for agile implementation.
  • 4. ML Deployment & Maintenance
    • Lead the deployment and monitoring of batch-based ML models.
    • Define standards for model execution, monitoring, and retraining workflows.
    • Collaborate with model builders for smooth model-to-production handoff.
  • 5. Automation & SLAs
    • Define and enforce SLAs for data, dashboard, and BRE changes.
    • Introduce automated solutions using tools like GenAI, n8n, dbt, CI/CD.
    • Continuously improve efficiency of analytics delivery.
  • 6. Team Leadership
    • Lead a small team (2–4 analysts/engineers) with responsibility for prioritization, quality, and development.
    • Conduct regular reviews, mentorship, and skill development.
    • Act as the bridge between business stakeholders and the analytics team.

Qualifications

  • 5–8 years of experience in analytics engineering / BI / data platforms.
  • Advanced SQL, data modeling, and pipeline orchestration experience.
  • Strong BI expertise (Tableau, PowerBI, Looker, or equivalent).
  • Hands-on with ML model deployment (batch pipelines, monitoring, scheduling).
  • Familiarity with cloud platforms (BigQuery, Snowflake, GCP/AWS/Azure).
  • Experience with workflow automation (Airflow, dbt, n8n, CI/CD).
  • Prior experience in leading small teams and stakeholder management.

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