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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
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.