
The Industry’s Largest Pure-Play Supply Chain Service Provider
Core focus: AI-powered application transformation for the digital/connected supply chain
Headquarters: San Jose, California
Employee count (reported): 3401
Ownership: Part of the Mahindra Group
Funding signal: One recorded Series B; lead investor listed as Ridgewood Capital (details obfuscated)
Digital transformation of supply chains and supply-chain application modernization
Supply chain consulting / digital supply-chain services
Funding details and amounts are obfuscated in available records.
“Part of the Mahindra Group”
We are seeking a talented and experienced Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and systems to support analytics and data-driven decision-making. This role requires expertise in data processing, data modeling, and big data technologies. * Design and develop datapipelines to collect, transform, and load data into datalakes and datawarehouses . * Optimize ETLworkflows to ensure data accuracy, reliability, and scalability. * Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements. * Implement and manage cloud − baseddataplatforms (e.g., AWS , Azure , or GoogleCloudPlatform ). * Develop datamodels to support analytics and reporting. * Monitor and troubleshoot data systems to ensure high performance and minimal downtime. * Ensure data quality and security through governance best practices. * Document workflows, processes, and architecture to facilitate collaboration and scalability. * Stay updated with emerging data engineering technologies and trends. * Strong proficiency in SQL and Python for data processing and transformation. * Hands-on experience with bigdatatechnologies like ApacheSpark , Hadoop , or Kafka . * Knowledge of datawarehousingconcepts and tools such as Snowflake , BigQuery , or Redshift . * Experience with workfloworchestrationtools like ApacheAirflow or Prefect . * Familiarity with cloudplatforms (AWS, Azure, GCP) and their data services. * Understanding of datagovernance , security , and compliance best practices. * Strong analytical and problem-solving skills. * Excellent communication and collaboration abilities. * Certification in cloudplatforms (AWS, Azure, or GCP). * Experience with NoSQLdatabases like MongoDB , Cassandra , or DynamoDB . * Familiarity with DevOpspractices and tools like Docker , Kubernetes , and Terraform . * Exposure to machinelearningpipelines and tools like MLflow or Kubeflow . * Knowledge of datavisualizationtools like PowerBI , Tableau , or Looker .