Renew Home is seeking an experienced Data Engineering Manager to lead a team in building and maintaining secure, scalable data infrastructure and pipelines to support their growing business needs in managing residential energy.
Requirements
- Hands-on experience in building and managing scalable batch and real-time data pipelines using structured and unstructured data, with familiarity in orchestration tools like Prefect, Airflow, or Dagster, and gaining proficiency in all areas of the product and technology applications.
- Expertise in streaming technologies such as Apache Kafka, AWS Kinesis, Apache Flink, or GCP Pub/Sub.
- Strong knowledge of data lake architectures and technologies (e.g., AWS S3, AWS Glue, Delta Lake, or similar), knowledgeable of multiple product areas with depth in 2+ areas, and able to develop specific, well-defined problem statements for large unstructured problems.
- Demonstrated ability to lead database performance analysis and optimization, including query tuning, indexing, and resource management, preferably with Redshift and Postgres, as a point person on at least one key area.
- Proficiency in infrastructure-as-code tools like CDK and Terraform for automating deployments and management.
- Solid software engineering foundation with proficiency in programming languages such as Python, Java, PHP, or Ruby, and the ability to design to spec and deliver full-featured products or modules.
- Manage the team's work across our technology stack, including Python,, Postgres, AWS/GCP services (CDK, ECS/EKS, RDS, Redshift, zeroETL,, S3 Tables, Athena, Iceberg, Glue, Flink, S3, SQS, SES, Pub/Sub, etc.), Prefect, Redis, Git, and Jira, demonstrating depth in 2+ areas and expertise in at least one layer of the technology stack.
Responsibilities
- Architect and oversee the deployment of secure, scalable, and highly available batch and real-time data pipelines, ensuring alignment with business objectives and best practices, while personally delivering significant features and breaking down work into manageable deliverables.
- Guide the implementation and optimization of data lake architectures for handling structured and unstructured data from millions of thermostats, delegating tasks while maintaining overall accountability, and applying knowledge of the company's business to competitive advantage.
- Ensure the team strives for and achieves 99.99% uptime SLA for data systems, including managing and participating in on-call rotations, incident response, and the preparation of detailed incident reports, while providing solutions that meet standards of operational excellence.
- Uphold data quality, integrity, and compliance with governance standards, implementing processes and tools to monitor and enforce these across the team, and making recommendations for headcount planning.
- Manage the team's work across our technology stack, including Python,, Postgres, AWS/GCP services (CDK, ECS/EKS, RDS, Redshift, zeroETL,, S3 Tables, Athena, Iceberg, Glue, Flink, S3, SQS, SES, Pub/Sub, etc.), Prefect, Redis, Git, and Jira, demonstrating depth in 2+ areas and expertise in at least one layer of the technology stack.
- Lead and mentor a team of data engineers, providing technical guidance, career development, and performance feedback to foster a high-performing and collaborative environment, including understanding leadership nuances, contributing to job descriptions, hiring plans, and participating in reviews and performance management actions.
- Collaborate with development teams, data scientists, analysts, and other cross-functional stakeholders to integrate data engineering services into the broader system architecture and deliver clean, reliable data, advocating for technical solutions and motivating the team.
Other
- Lead and mentor a team of data engineers, providing technical guidance, career development, and performance feedback to foster a high-performing and collaborative environment, including understanding leadership nuances, contributing to job descriptions, hiring plans, and participating in reviews and performance management actions.
- Comfort balancing leadership and technical execution. Willing to engage directly in design and implementation work while effectively managing, mentoring, and enabling the team.
- Excellent leadership and communication skills, with experience in mentoring engineers, collaborating across teams, providing guidance on data infrastructure best practices, motivating smaller teams, and presenting to larger groups as part of a team.
- Commitment to fostering a culture of continuous learning, keeping the team updated on advancements in cloud infrastructure, database technologies, and data engineering processes, while understanding your own leadership style and leveraging it to develop and manage small teams.
- Ability to make decisions with incomplete data and understand when it's important to act without a clear choice, while being comfortable with ambiguous situations.
