Senior Software Engineer (Data/Backend)

Requirements

• 5+ years of industry experience in backend and data engineering, with demonstrated expertise delivering scalable, high-performance systems in fast-paced, enterprise-level environments.
• Strong programming skills in at least two of TypeScript/Node.js, Python, and Go, with experience building and maintaining microservices architectures on Kubernetes.
• Hands-on experience building and operating production ETL/ELT and streaming data pipelines, including workflow orchestration (e.g., Airflow, Dagster) and stream processing (e.g., Kafka Streams, Flink, or Spark).
• Experience with data warehouse/lakehouse technologies (e.g., Snowflake, BigQuery, Redshift, or S3 with Parquet/Iceberg), including analytical data modeling for large datasets.
• Strong expertise in database management, with experience in schema design, performance tuning, and indexing for large-scale distributed databases (e.g., PostgreSQL, MongoDB, or Cassandra).
• Experience with message- and event-driven architectures using tools like Kafka, RabbitMQ, or other event-streaming systems to build highly scalable, decoupled services.
• Expertise in designing and consuming APIs (REST, GraphQL, or gRPC), with a focus on creating secure, scalable, and high-performance services.
• Commitment to data quality and observability — pipeline testing, monitoring, alerting, and lineage — with hands-on experience using Prometheus and Grafana to maintain system performance and health.
• Experience with cloud-native technologies on AWS (e.g., Lambda, S3, EKS/ECS, Kinesis, SQS) and designing for cost-efficient operation at scale.
• Hands-on experience with CI/CD pipelines (Jenkins, GitLab, or similar), automating testing, deployment, and scaling of services.
• A deep understanding of security best practices, such as securing APIs, handling sensitive data, and managing authentication/authorization (OAuth, JWT).
• Strong desire to work in a fast-paced, start-up environment with multiple releases a day, and experience working in an Agile development environment — leading sprint planning, breaking down large initiatives, and aligning team efforts with business objectives.
• Exceptional analytical and problem-solving abilities, with a proven track record of diagnosing complex issues, devising effective solutions, and implementing innovative approaches to overcome technical challenges.
• Demonstrated ability to leverage AI-assisted development tools to accelerate delivery while maintaining rigorous code quality, security review, and architectural integrity.

Nice to Have