Senior Product & Data Engineer

As a Senior Product & Data Engineer at Data-Hat AI, you will play a crucial role in designing, building, and deploying the backend services that power Orkestra's retail AI platform. Your responsibilities will include working with Microsoft Azure, AWS, and GCP to build APIs, workflow engines, action-tracking services, integration layers, and customer-facing data products. You will also be tasked with turning product requirements and customer needs into technical designs and deployable features. Key Responsibilities: - Design, build, and deploy backend services using Microsoft Azure, AWS, and GCP - Create APIs, workflow engines, action-tracking services, integration layers, and customer-facing data products - Work with Databricks, Delta Lakes, Lakehouse, and medallion architectures - Turn product requirements and customer needs into technical designs - Build reliable integrations with various data sources and third-party APIs - Investigate data issues using SQL and Python - Map customer source data into Orkestra's retail data model - Develop data-quality checks, alerting, retry logic, and reconciliation processes - Own service reliability, logging, monitoring, tracing, error handling, and production debugging - Build deployment pipelines across different environments - Collaborate with retail experts to ensure data outputs are commercially credible - Contribute to engineering standards around testing, CI/CD, code review, release management, and documentation Qualifications Required: - 6+ years of hands-on engineering experience - Strong proficiency in Python, SQL, and practical data investigation - Experience with cloud deployment on Azure, AWS, or GCP - Knowledge of Docker, CI/CD, Git workflows, and automated testing - Familiarity with authentication, authorisation, secure API design, and secrets management - Experience with asynchronous workflows, queues, schedulers, and idempotent processing The following experiences are valuable but not mandatory: - Experience with retail, ecommerce, inventory, supply-chain, ERP, POS, or warehouse systems - Knowledge of Databricks, Spark, Delta Lake, or data-platform architecture - Experience deploying AI or ML-enabled products in production - Familiarity with workflow orchestration and agentic workflows - Experience building multi-tenant SaaS products for enterprise customers As a Senior Product & Data Engineer, you will thrive in this role if you: - Have deployed systems used by real customers - Can work from an outcome, not just a fully specified ticket - Care about data reconciliation and practical product workflows - Know how to balance speed, reliability, cost, and technical debt - Can effectively communicate technical issues to non-technical colleagues - Take ownership of deployment and operational quality - Write clear documentation and ensure maintainable systems Data-Hat AI is building Orkestra, an AI-native operating system for retail. This contract role is based in Bangalore, but candidates from anywhere in India will be considered. As a Senior Product & Data Engineer at Data-Hat AI, you will play a crucial role in designing, building, and deploying the backend services that power Orkestra's retail AI platform. Your responsibilities will include working with Microsoft Azure, AWS, and GCP to build APIs, workflow engines, action-tracking services, integration layers, and customer-facing data products. You will also be tasked with turning product requirements and customer needs into technical designs and deployable features. Key Responsibilities: - Design, build, and deploy backend services using Microsoft Azure, AWS, and GCP - Create APIs, workflow engines, action-tracking services, integration layers, and customer-facing data products - Work with Databricks, Delta Lakes, Lakehouse, and medallion architectures - Turn product requirements and customer needs into technical designs - Build reliable integrations with various data sources and third-party APIs - Investigate data issues using SQL and Python - Map customer source data into Orkestra's retail data model - Develop data-quality checks, alerting, retry logic, and reconciliation processes - Own service reliability, logging, monitoring, tracing, error handling, and production debugging - Build deployment pipelines across different environments - Collaborate with retail experts to ensure data outputs are commercially credible - Contribute to engineering standards around testing, CI/CD, code review, release management, and documentation Qualifications Required: - 6+ years of hands-on engineering experience - Strong proficiency in Python, SQL, and practical data investigation - Experience with cloud deployment on Azure, AWS, or GCP - Knowledge of Docker, CI/CD, Git workflows, and automated testing - Familiarity with authentication, authorisation, secure API design, and secrets management - Experience with asynchronous workflows, queues, schedulers, and idempotent processing The following experiences are v