Data engineering and supply chain consulting for enterprise clients
Syren is a data engineering and supply chain consultancy serving Fortune 500 and high-tech clients. The tech stack reveals a mature Azure-first analytics operation (Data Factory, Databricks, Delta Lake, MLflow) paired with active AI/ML adoption (LangChain, AutoGen, LlamaIndex, LangGraph), suggesting a shift toward LLM-powered applications within data pipelines. Current hiring focuses on engineering and data roles across the US and India, with leadership-level positions open—consistent with scaling infrastructure-as-code initiatives and addressing known friction points around data incidents and transformation complexity.
Syren delivers data engineering, supply chain optimization, and AI consulting to large enterprises and technology leaders. Founded in 2020, the company operates development centers in the United States and India, with 201–500 employees based in Bellevue, Washington. The firm's service portfolio spans supply chain strategy, data consulting, data science, AI, and software engineering. Active projects include demand forecasting models, recommendation engines, lakehouse administration, WMS implementations, and cloud migration work (particularly legacy-to-Databricks transitions). Core challenges they're navigating internally—data ingestion, transformation bottlenecks, scaling, and regulatory compliance—mirror the problems their clients face.
Syren's primary stack: Azure (Data Factory, Data Lake Storage, DevOps), Databricks, PySpark, Python, SQL, Delta Lake, MLflow, Power BI, and GCP/AWS for multi-cloud support. CI/CD runs on Jenkins, GitHub, GitLab, and Azure DevOps with security scanning via SonarQube.
Current projects: demand forecasting, recommendation engines, ETL/lakehouse pipelines on Databricks, infrastructure-as-code provisioning, CI/CD security gates, regulatory compliance integration, and end-to-end WMS implementation. Also adopting LLM frameworks (LangChain, AutoGen, LlamaIndex) for model integration.
Other companies in the same industry, closest in size