We are seeking another skilled engineer passionate about architecting robust and scalable data solutions. In this role, you’ll be instrumental in building and refining the backbone of our data infrastructure, enabling critical backend services and large-scale analytics.
Role Overview
You’ll collaborate across teams to design, implement, and maintain systems that handle high-throughput data ingestion, processing, and storage. This position goes beyond traditional data engineering, offering the opportunity to influence the core architecture that supports our API and analytics capabilities at massive scale.
Key Responsibilities
Lead initiatives focused on improving data synchronization, storage efficiency, data enrichment, and analytics workflows.
Develop and enhance both streaming and batch data pipelines that underpin our main products and APIs.
Architect storage frameworks capable of managing substantial volumes of IoT and time-series information.
Maintain and evolve real-time systems to accommodate rapidly increasing data streams.
Apply distributed tracing and observability best practices to strengthen system monitoring and diagnostics.
Deliver high-quality, maintainable solutions using Java and Node.js within our platform ecosystem.
Contribute to high-level architectural strategies to ensure the platform’s scalability, reliability, and performance.
Requirements
Qualifications
At least 4 years of experience in platform or data engineering roles.
Minimum 2 years working on large-scale data pipeline design and optimization (terabyte to petabyte scale).
Demonstrated expertise in system architecture, particularly data-centric workflows.
Knowledge of modern data lakehouse technologies (such as Iceberg, Delta, Hudi, or Snowflake).
Hands-on experience with real-time data processing frameworks (e.g., Kafka, Spark, Flink).
Solid understanding of distributed computing and large-scale data management.
Proficiency in Java, with an emphasis on writing maintainable and efficient code.
Strong analytical and collaborative skills.
Technology Stack
Category
Tools & Technologies
Languages
JavaScript, TypeScript, Java
IaC
SST, AWS CDK
Compute & Orchestration
AWS Lambda, Step Functions
Storage
Amazon S3, DynamoDB
Messaging & Events
Amazon SQS, EventBridge
Data Processing
AWS Glue, Flink, Kafka, Iceberg, DuckDB
CI/CD
GitHub Actions
If you are eager to drive innovation on a high-impact data platform and enjoy solving diverse engineering challenges, we encourage you to apply.
