Senior Data Engineer

Summary

Join our extraordinary team at ecobee, a rapidly growing global tech company, as we build the world of tomorrow with solutions that improve everyday life while making a positive impact on the planet. We're looking for curious, talented, and passionate people to join our dynamic data engineering and machine learning services focused group.

Requirements

• Proficiency in building data pipelines using Python, SQL , and tools like Apache Spark, Apache Kafka, and Apache Airflow
• Experience with cloud-based data platforms ( GCP preferred), including services like Big Query, Big Table, and Dataflow
• Familiarity working with SQL based operational databases like
• Familiarity with data processing and storage solutions tailored for machine learning workflows
• Good understanding of the machine learning lifecycle and experience in supporting data preparation, feature engineering, and model deployment processes
• Experience working with machine learning frameworks and libraries is a plus
• Strong experience in data modeling, schema design, and optimization for data warehousing and data lake solutions
• Experience with designing data solutions that support both batch and real-time processing requirements
• Excellent communication skills, with the ability to work effectively in a collaborative environment and convey technical concepts to non-technical stakeholders
• Proven track record of working in cross-functional teams and driving alignment between technical and business goals

Responsibilities

• Design, build, and maintain scalable and efficient ETL / ELT pipelines for both batch and real-time data ingestion and transformation
• Implement data extraction and processing solutions to support analytics, machine learning, and operational use cases
• Integrate diverse data sources, including IoT device data, third-party APIs, and internal systems, into centralized data repositories
• Develop and maintain data warehousing solutions and ensure data is structured and available for downstream analytics
• Monitor and optimize data workflows and infrastructure to ensure high performance and reliability
• Implement monitoring, alerting, and logging for data pipelines to proactively identify and resolve issues
• Collaborate with data scientists, analysts, product managers, and other engineering teams to understand data requirements and deliver high-quality data solutions
• Translate business requirements into technical specifications and provide guidance on data engineering best practices
• Implement data quality checks, validation, and cleansing procedures to ensure data integrity and accuracy
• Create and maintain comprehensive documentation for data pipelines, architectures, and processes
• Share knowledge and best practices with the team, and contribute to the growth and development of the data engineering community within the organization
• Architect and implement sophisticated data pipelines that handle massive IoT data streams, ensuring data quality, consistency, and low-latency processing
• Introduce frameworks and best practices for feature engineering, data versioning, and experimentation in collaboration with machine learning teams

Benefits

• Competitive salaries
• Health benefits
• A progressive Parental Top-Up Program (75% top-up or five bonus days off)
• Flexible hours
• Remote work option