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Senior BI Developer

  • Hybrid
    • Bucharest, București, Romania

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.

Job 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).

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