Job Opportunities API

Overview:   We are looking for a Senior Data Engineer with deep expertise in Lakehouse architecture, real-time data streaming, cloud data infrastructure, and microservices development on Azure Kubernetes Service (AKS). You will play a central role in designing and delivering next-generation data pipelines, BI solutions, AI/ML platforms, streaming APIs, and scalable microservices that power Guidepoint's research and analytics products.   This is a high-impact, hands-on engineering role. You will work closely with data architects, data scientists, analysts, frontend engineers, QA, and DevOps teams to translate complex business requirements into scalable, reliable, and observable data systems.   This is a Hybrid role from our Pune office. What You'll Do: Data Engineering & Lakehouse   Design, build, and maintain ETL pipelines, data ingestion workflows, and table schemas on Azure Databricks to support BI, analytics, and AI/ML use cases   Architect and optimize the Lakehouse using Delta Lake on Databricks, ensuring reliability, performance, and cost efficiency   Build and support data pipelines from business applications such as Salesforce, NetSuite, and other enterprise systems   Develop and maintain Knowledge Graph models, entity relationship structures, and NLP-based insight pipelines   Maintain data governance, data privacy standards, and compliance best practices throughout the data lifecycle   Perform root cause analysis on data and processes to identify opportunities for improvement   Collaborate with data architects, scientists, and business consumers to populate and optimize the data warehouse for reporting and analytics   Microservices & AKS Development   Develop and support scalable web APIs and microservices using Python and Azure Platform Services   Build new applications, services, and platforms; optimize existing solutions and refactor legacy components using modern, scalable architectures   Design, implement, and deploy microservices on Azure Kubernetes Service (AKS) using Docker, Kubernetes, Helm, and Azure DevOps YAML pipelines   Perform end-to-end deployments including infrastructure setup, configuration, and monitoring on AKS   Decompose portions of legacy applications into modern microservices architecture   Design and manage JSON payloads and payload contexts for inter-service communication   Engage in database schema design and management, including updating tables and rows for large datasets   Collaborate with cross-functional teams — Full-Stack, QA, DevOps, and Product — in agile SDLC processes   Real-Time Streaming & SSE   Design and implement robust SSE (Server-Sent Events) endpoints using Python frameworks (FastAPI, Flask, Django) for real-time event delivery to web and mobile clients   Build and maintain asynchronous backend services using asyncio, aiohttp, or similar libraries for non-blocking, high-concurrency streaming   Architect streaming data pipelines integrating SSE with upstream message brokers — Kafka, Redis Pub/Sub, RabbitMQ   Optimize connection lifecycle management: reconnection logic, heartbeat signals, event ID tracking, and graceful shutdowns   Collaborate with frontend teams to define and evolve SSE event schemas and API contracts   Implement observability across streaming services: distributed tracing, structured logging, and metrics using Prometheus, Datadog, or OpenTelemetry   Engineering Excellence   Write comprehensive unit, integration, and load tests for all data, streaming, and microservices components