Job Description

Roles & Responsibilities:

• Design, build, and maintain scalable BI dashboards and reports using internal cutting edge AI LLM solution .
• Design, build, and maintain scalable ELT pipelines to ingest, transform, and load data from diverse sources into the data warehouse.
• Develop and maintain data models using dbt for transformation and RiveryQlik Replicate for ingestion , ensuring data quality, consistency, and documentation.
• Build and manage data infrastructure in Snowflake, including schemas, roles, access control, and performance optimization.
• Collaborate with analysts, data scientists, and business stakeholders to deliver reliable, well-structured data products supporting BI and ML workloads.
• Write clean, maintainable Python scripts for data processing, orchestration, and automation.
• Monitor pipeline health, troubleshoot issues, and drive continuous improvements to reliability and performance.
• Define and enforce data engineering best practices — including testing, CI/CD, versioning, and documentation.

Requirements

Requirements

• 5+ years of experience in BI Development or a closely related role.
• Experience with BI tools such as Tableau, Looker, Power BI, or QlikSense.
• Hands-on experience with Snowflake or an equivalent cloud data warehouse (BigQuery, RedshELTift, Databricks).
• Proficiency with ELT frameworks and patterns; experience with dbt or Rivery strongly preferred.
• Strong SQL skills — complex queries, performance optimization, and large-scale datasets.
• Experience designing and maintaining data models (dimensional, OBT, or similar) for analytical workloads.
• Experience with leverage AI capabilities (e.g., LLMs or predictive models) to enhance analytics, such as generating automated insights, natural language querying, anomaly detection, semantic models design & development
• Familiarity with orchestration tools such as Apache Airflow or equivalent.
• Strong understanding of data quality, testing practices, and observability.
• Ability to work independently and collaborate effectively in a cross-functional environment.
• Solid Python programming skills for pipeline scripting, API ingestion, and data validation (Advantage)
• Exposure to ML engineering or feature store concepts (Advantage).