Senior BI Developer
Confirmed on the employer's own hiring board on Sep 28, 2026. First seen by Alion on Jun 23, 2026. amsaccelerateit.com scores A on the Alion truth index.
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).