About Us DataWeave is a SaaS-based digital commerce analytics platform that empowers retailers with competitive intelligence and enables consumer brands to optimize their digital shelf performance at a global scale. Powered by proprietary AI technology, DataWeave processes over 500+ billion data points across 400,000+ brands, 4,000+ websites, and more than 20 industry verticals. Our customers include leading global retailers and brands such as Nordstrom, Overstock, The Home Depot, Mars, Bush Brothers, Mondelez, and Pernod Ricard. We are a globally distributed team of 220+ engineers, product managers, and eCommerce experts with our technology hub based in Bangalore.Role Overview We are seeking a Tech Lead / Associate Architect – Data Engineering to drive the design and implementation of scalable data platforms, ETL pipelines, and distributed data processing systems. The role involves close collaboration with product, data science, and analytics teams to build reliable data foundations that power business insights at scale.Key ResponsibilitiesDesign, build, and own end-to-end ETL pipelines for large-scale data ingestion, transformation, and processingArchitect scalable workflows integrating structured and unstructured data sourcesOptimize ETL frameworks for performance, scalability, and cost efficiencyLead integrations with Snowflake, Databricks, or similar analytical data platformsManage cloud-native deployments using Kubernetes and CI/CD pipelinesEnsure data quality, governance, monitoring, and reliability across data pipelinesCollaborate with product, data science, and analytics teams to translate requirements into engineering solutionsMentor and guide engineers on data engineering best practices, code quality, and architectureRequired Qualifications6–10 years of experience in data engineering or related rolesBachelor’s or Master’s degree in Computer Science, Information Systems, or equivalent experienceStrong expertise in Python with experience building production-grade systemsHands-on experience with distributed data frameworks such as PySpark and AirflowSolid experience with AWS services including S3, Athena, Lambda, and Step FunctionsStrong experience with data warehousing platforms such as Snowflake or DatabricksWorking knowledge of Kubernetes, Helm, and containerized deploymentsExposure to NoSQL databases such as MongoDB, DynamoDB, or CassandraExperience in query optimization, data partitioning, and large-scale data performance tuningFamiliarity with Git, CI/CD pipelines, and Infrastructure-as-Code tools such as Terraform or CloudFormationPreferred QualificationsExperience building data platforms for analytics, reporting, or AI/ML workloadsUnderstanding of modern data lakehouse architecturesExposure to data modeling and ELT design principlesStrong communication skills and ability to work with cross-functional stakeholders
Job Title
Associate Architect