The Senior Engineering Manager - Data Platform will lead and scale critical engineering teams responsible for streaming data infrastructure and big data platform capabilities. This role manages 10+ senior engineers across multiple teams, driving technical excellence and ensuring the delivery of robust, scalable data infrastructure that powers real-time and batch processing capabilities across the organization. You will be at the forefront of transforming traditional batch-oriented processes into real-time systems while building foundational data capabilities including storage infrastructure, streaming, data orchestration, big data processing, data warehousing, and real-time OLAP databases that enable data-driven decision-making company-wide.
Responsibilities
Design and build data platforms that promote standardization, including data pipeline development, platform tooling, data lake formatting, and data democratization Oversee development of real-time streaming platforms and complex stream processing topologies using latest open-source technologies Lead architectural decisions for stream processing, batch processing, and data infrastructure at scale Lead and manage high-performing engineering teams including senior individual contributors and technical leads Provide mentorship, career development, and performance management for engineers across different experience levels Foster a culture of technical excellence, innovation, and continuous learning Recruit, hire, and onboard top engineering talent to scale the teams effectively Drive the technical roadmap and long-term vision for data platform capabilities, ensuring alignment with business objectives Drive initiatives to improve existing tools to deliver value to platform users Collaborate closely with Data Science, BI, Product, and Engineering teams to understand requirements and deliver solutions Build strong cross-functional partnerships across the organization, influencing teams to adopt best practices Ensure high availability, scalability, and performance of data platforms supporting critical business operations Establish metrics, monitoring, observability, and visualization practices for data platform reliability
Qualifications
12+ years of software engineering experience with 4+ years in engineering management 4+ years of experience in open-source big data and streaming technologies on PB scale Experience scaling engineering teams and establishing effective development processes Deep expertise in streaming technologies: Apache Kafka, Kafka Streams, KSQL, Spark, Spark Streaming Strong understanding of distributed systems architecture and integration of operational systems with analytical systems Experience with cloud-based data infrastructure including AWS S3, streaming, data lakes, data warehouses, and OLAP databases Knowledge of data modeling, schema design, and experience with traditional, NoSQL and columnar databases Experience building scalable infrastructure to support stream, batch and micro-batch data processing Experience driving technical roadmaps and making strategic technology decisions at scale Excellent communication and presentation skills with ability to influence technical and business stakeholders Strong project management skills with experience leading large, complex initiatives across multiple teams Experience in data processing, orchestration, and data engineering best practices Knowledge of data governance, platform standardization, and data democratization principles
The salary for this position is between $204,000 and $255,000 per year, in compliance with California's salary transparency requirements. This range reflects the expected compensation based on qualifications, experience, and location. In addition to the salary, we offer a comprehensive benefits package, including:
Health, dental, and vision insurance 401(k) plan with company match Paid time off and holidays Professional development opportunities Flexible work arrangements For more, see www.benefitsatfanatics.comWe are committed to providing a supportive and inclusive work environment.