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.
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