Data Engineer

Data EngineerOur team is hiring a Data Engineer to join our EnerG team. Be a driving force behind our innovative cloud-based Building Management System (BMS) SaaS platform. You will play a pivotal role in shaping the future of energy management by architecting and developing the core data infrastructure. You will be at the forefront of processing and managing a high volume of data, handling billions of data points monthly to deliver insightful metrics and Key Performance Indicators (KPIs). Your contributions will directly empower our platform's ability to provide actionable energy insights. If you are a motivated Data Engineer with a strong passion for building and maintaining robust data infrastructure that facilitates seamless data processing, in-depth analysis, and impactful visualizations, we encourage you to explore this opportunity.What You Will Do:Design, develop, and maintain scalable data pipelines for efficient processing and storage of energy data.Implement data quality checks, monitor pipelines for issues, and ensure accuracy and completeness.Execute data cleaning processes to handle missing values, outliers, and inconsistencies, and standardize formats for consistency.Aggregate data at various intervals (e.g., 15-min, hourly, daily) and transform it into key metrics like energy consumption and cost analysis.Implement algorithms to detect and remove anomalies, ensuring the integrity of data-driven insights.Develop algorithms to create virtual meters by combining data from multiple sources or applying business rules.Enrich data with contextual information (e.g., weather, occupancy, utility rates) for deeper analysis.Identify and address data gaps to ensure comprehensive reporting and analysis.Analyze relationships between data sources to uncover correlations and insights for informed decision-making.Prepare data for dashboards, custom reports, and ad-hoc analysis; develop KPIs for ESG and energy metrics.Ensure compliance with industry standards like NABERS, LEED, and Energy Star for data collection and reporting.Normalize energy data based on external factors like weather to enable accurate comparisons.Develop predictive models to forecast energy consumption and support resource management planning.Requirements:Proven experience in designing and building end-to-end data pipelines.Hands-on experience with big data technologies, including but not limited to BigQuery, Apache Kafka, and Clickhouse.Proficiency in programming languages such as Python or Java, with a strong emphasis on data manipulation and processing.Demonstrated experience in building configurable and adaptable data pipelines to meet evolving business needs.A strong understanding of data modeling principles and best practices.Excellent analytical and problem-solving skills with a keen attention to detail.Ability to collaborate effectively within a team environment and communicate technical concepts clearly.A proactive approach to learning and adapting to new technologies and challenges in the data engineering landscape.Benefits:Competitive salary based on experienceDiscretionary Bonus ProgramCareer Development ProgramComprehensive Health Insurance PackageDynamic team and challenging projectsFlexible Paid Time OffWelcoming and friendly work environmentRegular social events and activitiesJoin the team:KODE Labs is a real estate technology company founded in 2017 with a mission to change the way people, buildings and systems operate. Headquartered in Detroit, Michigan, we are a driving force behind the adoption of smart building technology. To scale our presence in Detroit and across the Nation, we depend on our team of talented, ambitious people who go above and beyond to create value for our clients. When you join the KODE Labs team you can create your own career. Whether you have years of experience or are just starting, we help you realize your full potential and achieve your goals. If KODE Labs sounds like the place for you, we'd love to hear your story, so please apply through our online application form. Only shortlisted candidates will be contacted.