In this role, you will design, build, and operate the core data infrastructure that enables engineering teams to move fast while maintaining reliability, scalability, and operational excellence. You will work across databases, streaming systems, data lakes, cloud infrastructure, and platform services, solving complex challenges around scale, performance, and resilience.
As a senior engineer, you will play a key role in shaping our data architecture, driving technical decisions, and mentoring other engineers.
Responsibilities
Design, build, and operate scalable data platform services and infrastructure.
Develop high-quality software for distributed systems and data-intensive applications.
Design and optimize data storage solutions across operational databases, data lakes, and analytical systems.
Drive database performance improvements through query optimization, indexing strategies, schema design, and capacity planning.
Build and maintain event-driven architectures and streaming data pipelines.
Develop and improve data ingestion, transformation, orchestration, and processing frameworks.
Partner with product, engineering, analytics, and AI teams to deliver scalable and reliable data solutions.
Improve platform reliability, observability, and operational excellence through automation and engineering best practices.
Build and enhance CI/CD pipelines, deployment processes, and developer tooling.
Lead architecture discussions and contribute to long-term platform strategy.
Troubleshoot complex production issues and drive root-cause analysis and preventative improvements.
Mentor engineers through code reviews, technical guidance, and knowledge sharing.
Requirements
5+ years of experience building and operating large-scale backend, platform, or data infrastructure systems.
Strong programming skills in Python, Go, or Node.js.
Deep understanding of distributed systems, scalability, reliability, and performance optimization.
Strong experience with relational databases such as PostgreSQL or MySQL.
Strong experience with NoSQL databases such as MongoDB, DynamoDB, Cassandra, or similar technologies.
Proven experience optimizing database performance, query execution, indexing strategies, and large-scale data models.
Experience designing and operating data lakes and large-scale storage systems.
Experience building and maintaining data pipelines and ETL/ELT workflows.
Experience with event-driven architectures and messaging platforms such as Kafka.
Hands-on experience with cloud platforms, preferably AWS.
Experience with Docker, Kubernetes, and Infrastructure as Code tools such as Terraform.
Strong experience with monitoring, observability, and production troubleshooting.
Excellent communication and collaboration skills.
