<div class='\"job-descr' content> Who We Are Bidgely (which means \"electricity\" in Hindi) is an AI-powered SaaS Company accelerating a clean energy future by enabling energy companies and consumers to make data-driven energy-related decisions. Ranked #7 in Applied AI on Fast Company’s list of Most Innovative Companies in the World, Bidgely is putting customers at the center of the clean energy future. What We Do Powered by our unique patented technology, Bidgely's UtilityAI™ Platform transforms multiple dimensions of customer data - such as energy consumption, demographics, and interactions into deeply accurate and actionable consumer energy insights. We leverage these insights to empower each customer with personalized recommendations tailored to their individual personality and lifestyle, usage attributes, behavioral patterns, purchase propensity and beyond. How We Do It From a distributed energy resources (DER) and grid edge perspective, Bidgely is advancing smart meter innovation with data-driven solutions for solar PVs, electric vehicle (EV) detection, EV behavioral load shifting and managed charging, energy theft, short-term load forecasting, grid analytics and time of use (TOU) rate designs. Bidgely’s UtilityAI™ energy analytics provides deep visibility into generation and consumption for better peak load shaping and grid planning and delivers targeted recommendations for new value-added products and services. For more information, please visit <a href="%5C%22https://www.google.com/url?q=https://www.bidgely.com/&amp;source=gmail&amp;sa=D&amp;sa=E%5C%22">www.bidgely.com</a> or the Bidgely blog at <a href="%5C%22https://www.google.com/url?q=http://bidgely.com/blog&amp;source=gmail&amp;sa=D&amp;sa=E%5C%22">bidgely.com/blog</a>. How You Fit In Join our AWB Delivery &amp; Support POD as a Senior Data Analytics Engineer, specializing in energy analytics with a focus on power and current-related data. You'll be pivotal in analyzing large-scale datasets, detecting anomalies, and ensuring the operational stability of our energy analytics products. This role demands a proactive, analytical, and collaborative individual who can translate complex data into actionable insights and drive continuous improvement. Key Responsibilities: ● Data Analysis &amp; Production Support: Analyze extensive power and current datasets using Python/PySpark to identify trends, anomalies, and data gaps. Conduct a thorough gap analysis to pinpoint data inconsistencies and recommend effective corrective actions. Optimize data pipelines and transformations using Snowflake and dbt. Provide critical production support by validating data quality and ensuring smooth deployment of releases. Rapidly troubleshoot and resolve data inconsistencies and production incidents. Proficiency in SQL and Data Testing. Perform testing on data ingestion pipelines for a variety of data sources. Perform testing on Datawarehouse loads and reports generated from the Datawarehouse data. Can grasp data science concepts and verify data accuracy ● Post-Release Monitoring &amp; Performance Analysis: Continuously monitor data pipelines, transformations, and analytics performance post-deployment. Identify, document, and track defects and issues, working closely with the development team to ensure timely resolution. Implement and refine automated anomaly detection systems to proactively identify and mitigate potential issues. Collaborate with product and engineering teams to enhance data reliability and performance. ● Collaboration &amp; Communication: Work closely with Product Managers, Engineers, QA, and Business Stakeholders to align on requirements and drive improvements. Clearly and concisely communicate data-driven insights to both technical and non-technical stakeholders. Actively participate in stakeholder discussions to refine data models and maximize business impact. ● Documentation &amp; Release Management: Maintain comprehensive documentation of data models, transformation logic, and anomaly detection processes. Generate detailed release notes for data-related updates, including pipeline, transformation, and analytics model changes. Utilize Git, Confluence, and Notion for version control and collaborative documentation. Required Skills &amp; Experience: ● Extensive hands-on experience in Python/PySpark/ for large-scale data analysis. ● Proven expertise in anomaly detection, data quality validation, and gap analysis. ● Deep understanding of energy-related data (power, current, load research, grid data, EV analytics, etc.). ● Strong proficiency with Snowflake and dbt for data engineering. ● Experience with ETL pipeline tools like Airflow, and DBT. ● Expertise in advanced SQL and data analysis. ● Experience developing and maintaining data warehouses/Data Marts/PUB SUB models. ● Database development experience using Hadoop, RDS, or BigQuery and experience with various relational, NoSQL, and cloud data lake technologies. ● Familiarity with production support workflows, post-release monitoring, and issue debugging. ● Excellent written and verbal communication skills. ● Proficiency with Git, Confluence, and Notion. ● Strong understanding of non-functional requirements mostly related to security, performance and scale etc. ● Understanding of cost and cloud performance metrics in AWS, Snowflake etc. ● Exposure to Agile development methodologies. ● Ability to collaborate across teams and strong interpersonal skills. Preferred Skills: ● Experience with BI tools (Tableau, Power BI, Looker, Shiny). ● Big Data Development experience using Hive, Impala, Spark, and familiarity with Kafka. ● Comprehension of data science quality control processes What You Get Perks <ul> <li>Growth Potential with a Startup: Seize the opportunity to grow with an innovative startup</li> <li>Collaborative Environment: Work with a passionate team united by the goal of a clean energy future</li> <li>Unique Tools: We provide all the tools you need to excel in your role</li> <li>Group Health Insurance, Internet/Telephone Reimbursement, Professional Development Allowance, Gratuity etc</li> <li>Mentorship Programs: Opportunity to learn and receive mentorship from industry experts</li> <li>Flexible Work Arrangements: Benefit from flexible working arrangements, Work anywhere from India</li> </ul> Diversity, Equity, Inclusion and Equal Opportunity Bidgely is an equal-opportunity employer. We are serious about and embrace diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills to build a better future and a better workforce. Our hiring decisions are based on your skills, talent, and passion – not on your background, gender, race, age, or the quirky way you dance at office parties. Bidgely is an EVerify employer. </div>

Bidgely (which means "electricity" in Hindi) is a highly energetic and innovative startup working on something that has never been done before. They have developed ground-breaking analytics that can itemize home energy usage data to the appliance level without using any plug-level monitors. Now, they are setting out to deliver this technology to millions of households across the world and help save energy on a massive scale.

Data Analytics Engineer-AWB

<div class="\&quot;job-descr"> Who We Are Bidgely (which means \"electricity\" in Hindi) is an AI-powered SaaS Company accelerating a clean energy future by enabling energy companies and consumers to make data-driven energy-related decisions. Ranked #7 in Applied AI on Fast Company’s list of Most Innovative Companies in the World, Bidgely is putting customers at the center of the clean energy future. What We Do Powered by our unique patented technology, Bidgely's UtilityAI™ Platform transforms multiple dimensions of customer data - such as energy consumption, demographics, and interactions into deeply accurate and actionable consumer energy insights. We leverage these insights to empower each customer with personalized recommendations tailored to their individual personality and lifestyle, usage attributes, behavioral patterns, purchase propensity and beyond. How We Do It From a distributed energy resources (DER) and grid edge perspective, Bidgely is advancing smart meter innovation with data-driven solutions for solar PVs, electric vehicle (EV) detection, EV behavioral load shifting and managed charging, energy theft, short-term load forecasting, grid analytics and time of use (TOU) rate designs. Bidgely’s UtilityAI™ energy analytics provides deep visibility into generation and consumption for better peak load shaping and grid planning and delivers targeted recommendations for new value-added products and services. For more information, please visit <a href="%5C%22https://www.google.com/url?q=https://www.bidgely.com/&amp;source=gmail&amp;sa=D&amp;sa=E%5C%22">www.bidgely.com</a> or the Bidgely blog at <a href="%5C%22https://www.google.com/url?q=http://bidgely.com/blog&amp;source=gmail&amp;sa=D&amp;sa=E%5C%22">bidgely.com/blog</a>. How You Fit In Join our AWB Delivery &amp; Support POD as a Senior Data Analytics Engineer, specializing in energy analytics with a focus on power and current-related data. You'll be pivotal in analyzing large-scale datasets, detecting anomalies, and ensuring the operational stability of our energy analytics products. This role demands a proactive, analytical, and collaborative individual who can translate complex data into actionable insights and drive continuous improvement. Key Responsibilities: ● Data Analysis &amp; Production Support: Analyze extensive power and current datasets using Python/PySpark to identify trends, anomalies, and data gaps. Conduct a thorough gap analysis to pinpoint data inconsistencies and recommend effective corrective actions. Optimize data pipelines and transformations using Snowflake and dbt. Provide critical production support by validating data quality and ensuring smooth deployment of releases. Rapidly troubleshoot and resolve data inconsistencies and production incidents. Proficiency in SQL and Data Testing. Perform testing on data ingestion pipelines for a variety of data sources. Perform testing on Datawarehouse loads and reports generated from the Datawarehouse data. Can grasp data science concepts and verify data accuracy ● Post-Release Monitoring &amp; Performance Analysis: Continuously monitor data pipelines, transformations, and analytics performance post-deployment. Identify, document, and track defects and issues, working closely with the development team to ensure timely resolution. Implement and refine automated anomaly detection systems to proactively identify and mitigate potential issues. Collaborate with product and engineering teams to enhance data reliability and performance. ● Collaboration &amp; Communication: Work closely with Product Managers, Engineers, QA, and Business Stakeholders to align on requirements and drive improvements. Clearly and concisely communicate data-driven insights to both technical and non-technical stakeholders. Actively participate in stakeholder discussions to refine data models and maximize business impact. ● Documentation &amp; Release Management: Maintain comprehensive documentation of data models, transformation logic, and anomaly detection processes. Generate detailed release notes for data-related updates, including pipeline, transformation, and analytics model changes. Utilize Git, Confluence, and Notion for version control and collaborative documentation. Required Skills &amp; Experience: ● Extensive hands-on experience in Python/PySpark/ for large-scale data analysis. ● Proven expertise in anomaly detection, data quality validation, and gap analysis. ● Deep understanding of energy-related data (power, current, load research, grid data, EV analytics, etc.). ● Strong proficiency with Snowflake and dbt for data engineering. ● Experience with ETL pipeline tools like Airflow, and DBT. ● Expertise in advanced SQL and data analysis. ● Experience developing and maintaining data warehouses/Data Marts/PUB SUB models. ● Database development experience using Hadoop, RDS, or BigQuery and experience with various relational, NoSQL, and cloud data lake technologies. ● Familiarity with production support workflows, post-release monitoring, and issue debugging. ● Excellent written and verbal communication skills. ● Proficiency with Git, Confluence, and Notion. ● Strong understanding of non-functional requirements mostly related to security, performance and scale etc. ● Understanding of cost and cloud performance metrics in AWS, Snowflake etc. ● Exposure to Agile development methodologies. ● Ability to collaborate across teams and strong interpersonal skills. Preferred Skills: ● Experience with BI tools (Tableau, Power BI, Looker, Shiny). ● Big Data Development experience using Hive, Impala, Spark, and familiarity with Kafka. ● Comprehension of data science quality control processes What You Get Perks <ul> <li>Growth Potential with a Startup: Seize the opportunity to grow with an innovative startup</li> <li>Collaborative Environment: Work with a passionate team united by the goal of a clean energy future</li> <li>Unique Tools: We provide all the tools you need to excel in your role</li> <li>Group Health Insurance, Internet/Telephone Reimbursement, Professional Development Allowance, Gratuity etc</li> <li>Mentorship Programs: Opportunity to learn and receive mentorship from industry experts</li> <li>Flexible Work Arrangements: Benefit from flexible working arrangements, Work anywhere from India</li> </ul> Diversity, Equity, Inclusion and Equal Opportunity Bidgely is an equal-opportunity employer. We are serious about and embrace diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills to build a better future and a better workforce. Our hiring decisions are based on your skills, talent, and passion – not on your background, gender, race, age, or the quirky way you dance at office parties. Bidgely is an EVerify employer. </div>

Data Analytics Engineer-AWB

About the Job

About the Company

Bidgely

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