At Sonatus, we’re driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can’t keep pace with consumer expectations shaped by the mobile industry—where features evolve rapidly, update seamlessly, and improve continuously. That’s why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding.

Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we’re solving some of the most interesting and complex challenges in the industry. Join us and help redefine what’s possible as we shape the future of mobility.

We are seeking an experienced and highly skilled Senior Lead Database Engineer with deep expertise in both SQL and NoSQL databases, with a strong focus on time-series data, OLAP, and OLTP systems. This role is crucial for designing, implementing, and optimising high-performance, scalable database systems that support our data-intensive applications. As a Senior Lead Database Engineer, you will work closely with our data engineering, analytics, and product teams to ensure the reliability, scalability, and efficiency of our database infrastructure.

Key Responsibilities:

Design and Architecture:

Lead the design and architecture of robust, scalable, and high-performance database solutions, with a particular emphasis on time-series data, OLAP, and OLTP databases.
Evaluate and recommend appropriate SQL and NoSQL database technologies (e.g., PostgreSQL, TimeScale, Cassandra, Apache Druid, Apache Pinot) based on project requirements.
Design and implement data models that efficiently support a wide range of queries and data operations.

Database Development and Optimisation:

Develop, optimise, and maintain complex SQL queries, stored procedures, and indexing strategies to improve database performance.
Implement and manage time-series databases to handle high-frequency data ingestion and query processing.
Optimize OLAP/OLTP databases for performance, scalability, and reliability, ensuring minimal latency for transactional and analytical workloads.
Monitor and tune databases to ensure optimal performance, including query optimization, indexing, and storage management.

Data Management and Integration:

Work with cloud backend engineering teams to design ETL pipelines that move and transform data efficiently across different storage systems.
Implement data partitioning, sharding, and replication strategies to ensure high availability and scalability.
Ensure data integrity, consistency, and security across all database systems.

Collaboration and Leadership:

Collaborate with cross-functional teams, including AI Engineers, software engineers, and product managers, to understand data requirements and deliver database solutions that meet business needs.
Provide technical leadership and mentorship to junior engineers, guiding them in best practices for database design, development, and management.
Drive continuous improvement initiatives in database technologies, tools, and processes.

Research and Innovation:

Stay up-to-date with the latest advancements in database technologies, particularly in time-series and OLAP/OLTP systems.
Experiment with and evaluate new database technologies and tools to enhance our data architecture and infrastructure.
Contribute to the development of internal tools and frameworks to support database development and operations.

Qualifications:

Education and Experience:

Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
10+ years of experience in database engineering, with a strong focus on both SQL and NoSQL databases.
Proven expertise in designing and managing time-series databases (e.g., TimescaleDB, Apache Druid, Apache Pinot, etc) and OLAP/OLTP systems with high scale

Technical Skills:

Advanced proficiency in SQL, including query optimization, indexing, and stored procedure development.
Strong experience with NoSQL databases (e.g., MongoDB, Cassandra, Scylla, etc) and their respective data modeling techniques.
Deep understanding of time-series data concepts, architecture, and performance tuning.
Experience with OLAP technologies and tools such as Apache Druid, ClickHouse, or similar.
Familiarity with cloud-based database services (e.g., AWS RDS, Google Cloud BigQuery) and infrastructure as code (IaC) tools (e.g., Terraform, CloudFormation).
Strong programming skills (e.g., Golang, Java, Scala, etc).

Soft Skills:

Excellent problem-solving and analytical skills, with a keen attention to detail.
Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.
Leadership qualities with a proven ability to mentor and guide junior team members.

Preferred Qualifications:

Experience with streaming data platforms (e.g., Apache Kafka) and integrating them with time-series databases.
Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes) as they pertain to database deployment.
Experience with real-time analytics and data warehousing solutions.