Data/AI Engineer

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   Write and maintain robust CI/CD pipelines using Azure DevOps YAML pipelines   Participate in architecture reviews, code reviews, and on-call rotations   Maintain thorough technical documentation and mentor junior engineers on best practices in data engineering, Lakehouse architecture, streaming systems, and microservices   What You Have: Required   Bachelor's degree in Computer Science, Engineering, or a related field from an accredited university   7+ years of professional data engineering and/or backend software engineering experience   Advanced SQL expertise across relational and NoSQL databases (SQL Server, Neo4j, Elasticsearch, Cosmos DB)   Strong hands-on experience building and optimizing data pipelines on Azure Databricks   In-depth knowledge of Delta Lake, Data Warehousing, and Lakehouse architecture   Highly proficient in Spark, Python, and SQL   Proven experience designing and deploying microservices on AKS using Docker, Kubernetes, and Helm   Hands-on experience with Azure DevOps YAML pipelines for CI/CD automation   Experience with SSE or real-time streaming — event stream formatting, retry logic, connection management   Strong grasp of async Python: asyncio, async/await, event loops   Experience with message brokers: Kafka, Redis Streams, RabbitMQ, or similar   Proven track record of processing and extracting value from large, complex, and disconnected datasets   Excellent stakeholder management and communication skills across global, cross-functional teams   Proven leadership skills with a strategic mindset and passion for driving innovation   Nice to Have   Experience with Fivetran for data integration Familiarity with BI tools such as Power BI Experience building and deploying ML and feature engineering pipelines using MLflow Knowledge of Knowledge Graph development (e.g., Neo4j) and NLP-based analytics Familiarity with cloud-based AI/ML services and Generative AI tools Experience working in a compliance-based environment (building and deploying compliant software throughout the SDLC) Familiarity with API gateway configuration for streaming (NGINX, Kong, Azure API Gateway)   What We Offer:   Competitive compensation   Employee medical coverage   Central office location   Entrepreneurial environment, autonomy, and fast decisions   Casual work environment   About Guidepoint :   Guidepoint powers end-to-end research workflows for the world’s best research teams.   Backed by a global network of more than 2 million experts and over 1,600 employees, Guidepoint delivers real-time access to expertise, primary research, and actionable knowledge that help organizations make informed decisions. Through consultations, surveys, events, proprietary content, and AI-enabled tools, we support every stage of the decision-making process—from developing hypotheses and gathering insights to validating assumptions and building conviction for critical decisions.   At Guidepoint, our success relies on the diversity of our employees, experts, and clients, which enables us to foster meaningful connections and a broad range of perspectives. We are committed to creating an inclusive and welcoming environment where individuals of all backgrounds, identities, and experiences can contribute and succeed.     #LI-AD2 #LI-HYBRID    

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