What You Bring: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field. 5+ years of professional experience in Data Engineering or a related role. Strong experience designing and implementing large-scale data pipelines using orchestration frameworks such as Apache Airflow, Prefect, or similar. 5+ years of software development experience, including at least 2 years of Python development. Strong knowledge of relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, Elasticsearch/OpenSearch, ClickHouse, or similar technologies. Experience designing and implementing streaming and event-driven data architectures using technologies such as AWS Kinesis, Amazon SQS, RabbitMQ, Kafka, or similar messaging systems. Experience designing REST APIs and backend services (FastAPI or similar frameworks). Experience working with AWS cloud services (S3, EC2, Lambda, CloudWatch, IAM, etc.). Experience with Git, Docker, CI/CD pipelines, and modern software engineering practices. Excellent communication and collaboration skills with engineering, AI, and Product teams. Self-driven, innovative, and continuously looking for ways to improve systems and processes. Great to Have: Experience with Kubernetes and container orchestration. Experience with distributed computing platforms and distributed data processing systems. Experience building ML data pipelines supporting training and inference workloads. Experience working with large-scale sensor, IoT, or time-series data. Experience with monitoring and observability tools such as Grafana, Prometheus, ELK, Kibana, or OpenSearch. Experience working in edge computing or hybrid cloud environments.
