Top SQL Jobs in Pune

Build, test, deploy, and maintain production automations using n8n, custom code, AI models, PostgreSQL pipelines, and cloud platforms. Own automation initiatives end to end, integrate systems, monitor reliability and business outcomes, maintain CI/CD pipelines, respond to incidents, troubleshoot failures, and support security and compliance reviews. The role also involves stakeholder collaboration, process improvement, research into emerging automation technologies, and on-call participation.

Serves as the functional subject matter expert for Oracle Cloud PPM and financial operations. Leads requirements gathering, configuration, testing, implementation, support, issue resolution, quarterly update assessments, documentation, training, reporting, integrations, and data migration across Project Costing, Billing, Revenue Recognition, Budgeting, Project Management, and GL processes. Partners with Finance, PMO, IT, vendors, and business users to deliver compliant and effective Oracle Projects solutions.

Serves as the functional subject matter expert for Oracle Cloud PPM, configuring and supporting project costing, billing, revenue recognition, budgeting, forecasting, and project management processes. Leads requirements gathering, testing, implementations, quarterly updates, issue resolution, root-cause analysis, documentation, training, data migration, and audit support. Partners with Finance, PMO, IT, technical teams, and vendors while using OTBI, BI Publisher, FBDI, APIs, and SQL for reporting, troubleshooting, and data validation.

Support and troubleshoot production GCP data pipelines across batch and streaming workloads. Diagnose failures, latency, performance, and configuration issues; optimize pipelines for reliability and faster refreshes; support platform upgrades and compliance; and collaborate with Data Engineering, BI, and application teams. The role requires hands-on GCP, SQL, Python, BigQuery, Spanner, Dataflow, Pub/Sub, IAM, monitoring, logging, and production support experience.

Own marketing database operations for EMEA, including audience segmentation, data quality, privacy compliance, and performance analysis. Translate complex marketing data into actionable insights, recurring reports, and segmentation models. Partner with Marketing Operations, IT, and Data teams to improve database accuracy and processes, while enabling stakeholders through clear communication and training. The role requires strong SQL, marketing technology, project ownership, and business-facing analytical skills.

Design, build, and maintain centralized data pipelines, warehouses, lakes and hubs. Assemble complex datasets, implement ETL processes, build analytics tools and reports, support cross-functional teams, ensure secure cross-region data separation, and create product data tools to enable insights on acquisition and operational metrics.

Own the strategy, roadmap, and lifecycle of provider data management products, including directories, registries, master data, data quality, enrichment, and APIs. Translate customer and business needs into product requirements, guide discovery and delivery, define metrics, and collaborate with engineering, data science, analytics, UX, AI, and healthcare stakeholders. Use SQL, analytics, experimentation, and emerging technologies to improve provider data accuracy, operational efficiency, and customer outcomes.

Designs and oversees enterprise software architecture, development, testing, implementation, and technical documentation. Partners with stakeholders and Product teams to define requirements, evaluate technologies, create scalable solutions, review code, support application integrations, and guide development teams. The role also coordinates technology projects, training, system improvements, security, quality, and extensibility while providing technical support for case and client efforts.

Develop and extend SAP Hybris and Commerce Cloud e-commerce platforms, including Spartacus storefronts, backend services, custom extensions, workflows, and third-party integrations. Build scalable checkout, inventory, pricing, promotions, search, and cart features. Troubleshoot production issues, optimize high-volume performance, support cloud deployments, and maintain high availability through code reviews and engineering best practices.

Design, develop, and support scalable low-code applications on the Appian platform. Translate client requirements into process models, SAIL interfaces, records, reports, rules, data stores, and integrations. Troubleshoot defects, perform root-cause analysis, document technical solutions, and ensure compliance with Appian best practices, quality standards, and delivery procedures.

Leads multi-week to multi-month coding data programs for AI and platform teams. Responsibilities include designing coding assessments, coordinating software engineering fellows, building annotation and code-review workflows, managing QA and customer feedback, tracking delivery, margins and quality, and creating Python, TypeScript, and SQL automation for analytics and reporting.

Leads SAP Analytics Cloud and SAP BODS consulting engagements, including dashboard development, data modeling, ETL, data migration, production support, troubleshooting, and performance optimization. Collaborates with business, functional, technical, and client teams to gather requirements, design solutions, implement enhancements, manage integrations, and resolve incidents under SLA. The role requires expertise in SAC or BODS, SAP S/4HANA environments, data migration, relational databases, and technical documentation.

Design, develop, test, deploy, and maintain scalable Java and Spring Boot backend services, REST APIs, and microservices. Work with PostgreSQL, SQL, JPA/Hibernate, Azure, Docker, Kubernetes, and CI/CD pipelines. Apply distributed-systems, security, testing, observability, and performance practices. Troubleshoot production issues, contribute to architecture decisions, collaborate across technical teams, and mentor junior and mid-level engineers.

Build and maintain large-scale automated testing frameworks, libraries, infrastructure, and test suites for enterprise SaaS applications, APIs, services, and distributed systems. Integrate automation into CI/CD pipelines, troubleshoot application and production issues, validate AI-generated code and tests, improve coverage and reliability, and collaborate with engineering, DevOps, product, and QA teams. The role requires independently delivering extensive automation coverage and supporting issue reproduction outside standard hours when needed.

Designs and maintains large-scale automated testing frameworks, libraries, infrastructure, and suites for enterprise SaaS applications, APIs, services, and distributed systems. Integrates testing into CI/CD pipelines, troubleshoots application and production issues, validates AI-generated code, improves test coverage and reliability, and collaborates with engineering, DevOps, product, and QA teams. The role requires extensive hands-on programming, cloud experience, independent automation ownership, and occasional after-hours incident support.

Designs and maintains large-scale automated testing frameworks, libraries, infrastructure, and test suites for enterprise SaaS applications, APIs, services, and distributed systems. Develops production-quality automation, integrates tests into CI/CD pipelines, troubleshoots application and production issues, and expands test coverage using AI-assisted development tools. Collaborates with engineering, DevOps, product, and QA teams to improve reliability, observability, maintainability, and automation efficiency.

Develop and optimize secure, scalable backend APIs and database queries for FMS reporting. Responsibilities include architectural design, code reviews, mentoring, technical troubleshooting, performance tuning, CI/CD pipeline maintenance, production support, and Azure cloud integration. The role requires collaboration with architects, product managers, DevOps, QA, and business stakeholders while applying clean architecture, SOLID principles, secure coding practices, and modern .NET development techniques.

Own complex customer technical issues from investigation through resolution, specializing in JDBC integrations, databases, APIs, and data pipelines. Diagnose problems using SQL, logs, and product internals; partner with Engineering and Product on escalations and permanent fixes; lead incidents; improve support processes through automation and AI; create documentation; and mentor CX engineers.

Lead the architecture, development, deployment, monitoring, and support of scalable Java-based cloud-native platforms for investment banking and CRM/analytics. Build event-driven services, APIs, microservices, and real-time data pipelines using Kafka and multiple databases. Drive technical decisions, performance, resiliency, testing, observability, and CI/CD practices while mentoring engineers and collaborating with business, product, and global technology teams.

Own customer technical issues from investigation through resolution within SLA timelines. Troubleshoot SQL, databases, JDBC integrations, APIs, logs, and ETL workflows; communicate findings clearly and minimize escalations. Partner with Product and Engineering on complex issues, use AI and automation to improve support efficiency, and contribute to SOPs, knowledge-base articles, onboarding materials, training, and team enablement.

Design, develop, and support scalable Appian low-code applications, including SAIL interfaces, process models, records, reports, rules, and data stores. Translate client requirements into robust solutions, build REST/SOAP and JDBC integrations, troubleshoot defects, perform root-cause analysis, and maintain technical documentation, compliance, and quality standards.

Leads enterprise data architecture strategy and develops scalable data platforms, pipelines, warehouses, lakes, governance frameworks, and analytics solutions. Designs data models, integrations, migrations, and reporting architectures across AWS, Azure, Databricks, Snowflake, and BI platforms. Partners with AI/ML teams, business stakeholders, and senior leadership to modernize data capabilities, optimize performance, establish standards, and deliver complex analytical solutions. Mentors data engineers and architects while advancing data quality, security, compliance, and architectural governance.

Own budgeting, forecasting, financial modeling, management reporting, variance analysis, SaaS KPI analysis, and decision support for a growing SaaS business. Partner with finance and business stakeholders on profitability, pricing, ROI, and strategic initiatives. Support financial close, data integrity, controls, reporting automation, and audit requests while delivering actionable recommendations to leadership.

Own AI-driven software solutions end to end, from requirements discovery and architecture through development, testing, deployment, and support. Build cloud-native backends in Python, modern Angular or React frontends, and Azure infrastructure. Integrate data science models and AI agents into production systems, analyze business processes, lead validation and testing, provide documentation and technical support, and perform project planning and estimation.

Design, build, and maintain automated testing frameworks, infrastructure, and tooling for web, mobile, and API applications. Write automation code, integrate test suites into CI/CD pipelines, develop test strategies, identify edge cases, and perform functional, integration, regression, and performance testing. Build internal testing tools and collaborate with product managers and software engineers to improve feature testability and software quality.