Top SQL Jobs in Pune

Lead marketing analytics: own reporting frameworks, dashboards, and data quality; monitor KPIs; run A/B tests and experiments; build attribution, forecasting, segmentation, and budget-allocation models; automate workflows and drive continuous measurement improvements.

Build and maintain scalable batch and real-time data pipelines using Kafka, Maxwell, Spark and dbt; design medallion-based data models; implement cloud-native data platforms (S3, Trino, BigQuery); optimize performance, ensure data quality, observability, and SLA adherence; enable analytics through trusted datasets and Metabase dashboards.

Early-career software engineer role contributing backend/full-stack feature development, testing, CI/CD, and production releases. Collaborate on API/module design, system integration, and deployment. Support engineering of AI/LLM features (LLM APIs, basic RAG, embeddings/agents), maintain datasets/benchmarks, track performance, debug issues, and produce technical documentation.

Design, build, and maintain automated and exploratory tests for web and mobile apps. Create test plans, UI/API automation, compatibility and performance testing, perform root-cause analysis, improve test coverage, and develop testing tools and infrastructure to ensure product stability and user-focused quality.

Provide email, chat and phone support for account and billing issues, troubleshoot QoS and API problems, escalate and report bugs, perform billing reconciliations and audits, document knowledge base, and collaborate with cross-functional teams to resolve customer issues.

The Senior Data Scientist will engineer Zoom's Revenue Intelligence Engine, developing scalable systems for lead scoring and churn prediction while collaborating with various teams to provide data-driven insights.

Design, build, and deploy production-grade AWS data services and ETL pipelines using PySpark and AWS Glue. Perform data modeling, data warehousing, and advanced SQL development; automate CI/CD and Lambda workflows; work with Redshift/RDS and large datasets to extract and transform data for analytics.

Lead end-to-end AI/ML-driven transformation projects: translate business requirements, design experiments, analyze results, operationalize models with data science and engineering teams, drive agile delivery, stakeholder alignment, and mentor teams to deliver measurable business impact.

Lead end-to-end AI/ML-driven transformation projects: gather and translate requirements, design experiments, analyze results, partner with data science and engineering to operationalize models, drive agile project delivery, stakeholder alignment, and mentor teams to ensure measurable business impact.

Serve as a techno-functional business analyst: gather and translate requirements, design functional specifications, support integrations and data flows (APIs, databases, cloud), collaborate with architects and developers, support UAT and deployment, and drive process improvements and change management for digital transformation initiatives.

Analyze and model customer data using classical ML and NLP techniques, select algorithms, perform data wrangling and visualization, deploy models on cloud/big-data platforms, and communicate technical findings to non-technical stakeholders.

Design and drive end-to-end full-stack solutions across digital and manufacturing landscapes, ensuring compliance with GMP and security. Lead requirements, architecture, CI/CD, cloud integrations (AWS/Azure), and API development. Mentor teams, evaluate technologies, remediate technical debt, and guide agile delivery from design through deployment.

This role involves leading SAP data migration projects, developing ETL processes, ensuring data quality, and collaborating with cross-functional teams to optimize data integration and management strategies in SAP environments.

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

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.

Design and maintain ETL/ELT pipelines and data warehouse architecture, analyze and visualize data with SQL/Python/R and BI tools, build machine learning models and A/B tests, and partner with engineering and business teams to deliver data-driven insights for fintech use cases (fraud detection, segmentation, forecasting).

Lead Data Engineer to design, build, and operate production data pipelines, retrieval/vector infrastructure, semantic/feature stores, and ML/LLMOps foundations. Drive CI/CD, governance, monitoring, and agent/data APIs for RAG, LLM, and predictive model workloads.

Architect and own an enterprise AI-ready data platform: design lakehouse/data-mesh models, ingestion (streaming and batch), semantic/knowledge layers, retrieval/vector infra, LLMOps, governance, observability, and CI/CD to serve conversational AI, agents, BI copilots and ML models.

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

Build and scale backend services and orchestration for AI agents managing procure-to-pay workflows. Implement APIs, integrations with ERPs and payment systems, observability, auditability, secure data pipelines, and testing/eval frameworks to ensure reliable, compliant AI-driven operations at enterprise scale.

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

Design and deliver core capabilities for a cloud-native, distributed SQL platform. Build observable microservice applications, improve CI/CD and developer productivity, work on containers/Kubernetes and IaC, mentor engineers, and solve system-level database, networking, storage, and multi-tenant service challenges.

Design, build, monitor and scale an enterprise data warehouse and pipelines. Lead data integration, ETL design, source-to-target mapping, reusable frameworks, automated testing/CI, and partner with stakeholders to deliver secure, governed analytics for product, marketing and HR use cases.

Analyze large datasets, build ETL processes, create dashboards and data visualizations (Tableau) and present actionable insights to program leadership. Collaborate with stakeholders to define requirements and support data-driven decision making.

The Business Management Analyst assists in analyzing FTE and headcount management, supports job requests in Workday, conducts forecasting, and collaborates with teams for approvals and onboarding processes.