Build and own the semantic layer that powers analytics across customers, operations, commercial teams, and executive leadership.
Design, develop, and maintain dashboards, reports, and KPIs that support business decision-making and customer value visibility.
Define and measure customer outcome metrics, including ROI, energy savings, operational efficiencies, and avoided costs.
Translate business and operational requirements into scalable data models, reporting solutions, and analytical products.
Ensure data quality, consistency, lineage, governance, and reliability across analytical models and reporting assets.
Collaborate closely with Engineering to improve data structures, optimize analytical performance, and ensure data is analytics-ready.
Help drive the transition from traditional BI tools into native reporting experiences within the Keedian platform.
Contribute to the evolution of Keedian’s intelligence capabilities, including benchmarking, predictive analytics, fault detection, and optimization initiatives.
Document best practices and help scale the company’s analytics capabilities as the platform grows.

4+ years of experience in Analytics Engineering, Business Intelligence, Data Analytics, or related data roles.
Experience building semantic layers, reporting frameworks, or customer-facing analytics solutions.
Proven experience creating dashboards, KPIs, and reporting products from large datasets.
Experience working with time-series, telemetry, operational, or IoT-related data.
Experience collaborating with both technical and business stakeholders.
Experience owning analytics solutions end-to-end, from modeling through reporting.
Advanced SQL, including query optimization and data modeling.
Strong Python for data analysis and transformation.
Experience with dbt or similar data modeling frameworks.
Experience with BI and visualization tools such as Power BI, Tableau, Looker, or Metabase.
Experience working with AWS data services, including S3 and Athena.
Strong understanding of dimensional modeling and analytics engineering best practices.
Familiarity with data quality, testing, lineage, and governance concepts.

Experience with multi-tenant data platforms.
Exposure to statistics, experimentation, or predictive analytics.
Experience with machine learning fundamentals and tools such as scikit-learn.
Knowledge of IoT, smart buildings, energy management, HVAC systems, BACnet, Modbus, or related domains.
Experience with orchestration tools such as Airflow, Dagster, or Prefect.

Remote (Country)

Keedian is hiring a Senior Analytics Engineer