Top SQL Jobs in Pune

The Senior QA Engineer role involves designing and executing tests for web and mobile applications, identifying defects, contributing to automation, and ensuring the quality of deployments on Azure.

The Senior QA Engineer will design automation frameworks, drive test strategies, and ensure product reliability while mentoring juniors and collaborating with teams.

As a Data Scientist, assess business opportunities and promote data science use, developing and operationalizing analytics solutions with internal and external partners.

Maintain and enhance Oracle-based backend services and ADF/React frontends. Design and optimize SQL, build/consume REST and SOAP APIs, support testing/deployment and incident resolution, work with container concepts (Docker/Kubernetes), collaborate with stakeholders, and document changes following enterprise change management.

Lead the architecture and implementation of a distributed data platform for microscopy, ensuring scalability and high-performance in data management.

As a Data Engineer, you'll build and monitor large-scale data pipelines, develop the DBT setup for data transformation and solve customer problems using your SQL skills.

As a Lead Engineer, you'll design and develop frameworks and services for HighLevel's platform, optimizing large-scale database clusters and ensuring performance and security across multiple environments.

Work on SingleStore's database engine in small teams, building and testing production features. Projects may include query optimizer, SQL performance, fault tolerance, SIMD/LLVM codegen, and LLM/vector index integrations. Collaborate cross-functionally and own features end-to-end.

Design, train, validate, deploy and monitor ML models (pricing, dispatch, fraud, personalization). Perform EDA, feature engineering, statistical analysis, production-quality Python/SQL development, collaborate with product and engineering, and drive data quality, documentation, and knowledge sharing across the Data & AI domain.

The candidate will work with the PeopleSoft AMS team, focusing on Techno-Functional consulting for HCM or FSCM with 4+ years of experience.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

Develop and maintain Java-based cloud-native applications on AWS using Spring Boot, JPA/Hibernate, REST/SOAP. Implement serverless and microservice architectures (Lambda, Step Functions, API Gateway), integrate AWS services, perform RDBMS work, CI/CD, and front-end tasks. Collaborate in Agile teams and ensure testing, deployment, and monitoring automation.

Design, develop, and optimize SQL Server databases and ETL processes; troubleshoot and tune queries; ensure high availability, backups, deployments, and enforce database standards and documentation while collaborating with application and infrastructure teams.

Optimize and tune complex T-SQL queries, troubleshoot blocking/deadlocks and IO bottlenecks, analyze execution plans, implement indexing/partitioning, maintain HA/DR (Always On, clustering, replication), monitor database health and automation, and collaborate with developers on schema and query design.

Senior full‑stack engineer responsible for designing, developing, testing, and delivering scalable features using .NET Core and Angular on Azure PaaS. Collaborates with product, QA, and UX, drives architecture and CI/CD/DevOps practices, mentors junior engineers, and ensures performance, maintainability, and alignment with business roadmaps.

Design, build, and operate scalable data engineering services and ingestion pipelines (CDC/streaming). Develop and optimize a centralized analytics warehouse, data models, and aggregation strategies. Build APIs, enforce multi-tenant security and data governance, monitor pipeline health, improve automation and observability, and ensure production reliability through strong engineering practices.

Design and implement AI models, operationalize ML models, develop CI/CD pipelines for ML workflows, and provide technical guidance while ensuring data security compliance.

Designs and maintains enterprise dashboards and reports, performs SQL-based analyses, identifies operational performance drivers, partners with cross-functional leaders, provides ad-hoc analytics, and mentors junior analysts to improve organizational outcomes.

Lead process discovery and translate business needs into requirements. Design, configure, deploy, and maintain AI-driven workflows and agents using low-code/no-code platforms. Support UAT, RPA implementations, cross-platform automations, and stakeholder coordination while recommending technology improvements and ensuring integration with enterprise systems.

Lead a two-month project to assess the current data environment and design, build, and optimize a scalable cloud data warehouse. Deliver automated ETL/ELT pipelines, dimensional models, analytics-ready datasets, documentation, and handover while partnering with analysts and stakeholders for BI and reporting.

Lead cross-functional ML initiatives: choose modeling approaches, define business-linked evaluation metrics, validate with synthetic and real data, deliver MLOps-enabled models on AWS, ensure reproducibility, compliance, cost optimization, and incremental value within short agile release cycles.

Design, develop, and deploy data engineering solutions and analytics pipelines on Databricks. Build data models, optimize SQL and DAX queries, manage ETL and real-time ingestion, tune performance for large data volumes, and produce dashboards and reports while cross-training team members.

Lead cross-functional delivery of ML and analytics solutions: select modeling approaches, define business-aligned evaluation metrics, validate with synthetic and historical data, implement MLOps on AWS, ensure reproducibility, cost optimization, and regulatory explainability, and ship incremental value in short agile release cycles.

Lead design and delivery of production-grade agentic AI systems: discovery with clients, build multi-agent/ RAG pipelines, develop backend integrations, deploy and scale agent workloads on AWS, and implement safety, observability, and human-in-the-loop controls.

Design and develop SAC analytics applications and dashboards, build governed data models in SAP Datasphere, integrate varied data sources (including HANA), apply predictive features and scripting (SQL/Python/JavaScript), optimize performance, document BusinessObjects universes/reports, and provide technical leadership and Agile delivery for enterprise analytics use cases.