Senior Staff Software Engineer, AI Data Infra Lead

5 days ago

Pittsburgh, Pennsylvania, United States Stack AV Full time
About Stack:

Stack AV is a pioneering company in the development of revolutionary AI and advanced autonomous systems designed to enhance safety, reliability, and efficiency of modern operations. Our autonomous technology incorporates cutting-edge advancements in artificial intelligence, robotics, machine learning, and cloud technologies, empowering us to create innovative solutions that address the needs and challenges of the dynamic trucking transportation industry. With decades of experience creating and deploying real-world systems for demanding environments, the Stack AV team is dedicated to developing an autonomous solution ecosystem tailored to the trucking industry's unique demands.

About the Team:

Data is a crucial driver in the success of any ML company, and the autonomous vehicle industry is no exception. The AI Data Infra team, part of the ML Platform org of Stack AV, is responsible for storage, access, and curation of the data across the company and across all the ML use cases.

We are seeking an experienced, visionary, and hands-on technical lead for our data infra team. You will be responsible for designing the architecture and leading a team to build a robust data platform that powers all the next-gen AI Autonomous Vehicle applications in the company. The ideal candidate will have a deep understanding of modern data technologies, excellent leadership skills, and the ability to drive technical excellence.

Responsibilities:
1. Architectural Design: Design and oversee the architecture of the data platform, ensuring scalability, reliability, and performance.
2. Tech Leadership: Lead and mentor a team of data engineers in building and maintaining the data platform.
3. Data Management: Ensure efficient storage, retrieval, data quality, consistency, and governance across the platform. Develop and implement strategies for data lifecycle management, including archiving and purging.
4. Collaboration: Collaborate with cross-functional teams to understand data requirements and design appropriate solutions.
5. Technology Stack: Stay updated with the latest technologies and trends in data engineering, making recommendations for new tools and best practices.
6. Performance Optimization: Identify and resolve performance bottlenecks in data processing and storage.
7. Promote Engineering Excellence: Set a culture of engineering excellence within the team and work closely with the management and customer teams to balance between speed of delivery and quality of engineering artifacts.

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
8+ years of experience in data engineering or a related field, with at least 3 years in a technical leadership role.
Proficient in data architecture and design.
Extensive experience with data lake and data warehouse technologies (e.g., Hadoop, Spark, AWS S3, Redshift, Iceberg, Hive, Trino, etc).
Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).
Strong programming skills in languages such as Python, Java, or Scala.
Experience with ETL tools and processes.
Knowledge of machine learning and AI technologies and their data requirements.
Experience with agile development methodologies.
Contributions to open-source projects or technical publications.
Proven ability to lead and mentor a team, manage projects, and drive technical initiatives.
Strong analytical and problem-solving skills.
Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

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