Senior Analytics Engineer

🕒 June 2

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Keedian

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

☁️ SaaS

⚡ Energy

🤝 B2B

💰 $4.3M Series B on 2018-07

SaaS • Energy • B2B

Keedian is an intelligent operating system for multi-site building and asset operations. It integrates disparate building systems and sensors into a vendor-neutral platform that combines AI-enhanced workflows with human oversight to detect, resolve, and prevent operational issues. Keedian reduces truck rolls and downtime, optimizes energy use, and helps multi-site operators meet cost and sustainability goals across industries like grocery, retail, foodservice, and financial services.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 100% remote • Flexible schedule • Birthday day off • Reduced hours on Fridays • Unlimited vacations • Sick leave days • Moving day off • Support for studies, training, and language learning • Referral program