Top SQL Jobs in Pune

Develop and maintain advanced Power BI dashboards and reports for marketing analytics clients. Gather stakeholder requirements, define reporting solutions, transform and model data, implement Power BI Service features, and deliver actionable insights. Serve as the reporting subject matter expert, provide best-practice guidance, collaborate with data teams, support client presentations, and ensure reporting projects meet goals and milestones.

Leads complex enterprise integrations across Ivalua, ERP, HR, finance, logistics, and third-party systems. Responsibilities include end-to-end integration design, hands-on development, API and middleware implementation, performance optimization, troubleshooting, technical documentation, testing standards, customer workshops, pre-sales support, and mentoring. The role serves as a senior technical escalation point and helps establish reusable integration patterns, quality standards, and delivery practices across Professional Services projects.

Analyzes large datasets to identify trends, correlations, data-quality issues, and actionable business insights. Builds data pipelines, logical data models, interactive dashboards, visual reports, and automated reporting processes. Partners with stakeholders to recommend operational improvements, strengthen controls, and support data-driven decisions. The role also involves data integration, engineering, analytics, machine learning fundamentals, and payments-domain knowledge.

Design, build and maintain data pipelines, warehouses and lakes. Implement ETL processes, data models and processing algorithms. Ensure data accuracy, security and accessibility. Collaborate with data scientists, lead teams or projects, advise stakeholders, and drive risk controls and governance.

Business Analyst focused on data engineering and analytics, responsible for requirements gathering, stakeholder management, SQL analysis, data profiling, quality validation, reconciliation, reporting, and documentation. The role requires understanding ETL/ELT, pipelines, data warehousing, data modeling, databases, and Agile delivery. Experience with Python, PySpark, Airflow, cloud data platforms, APIs, and AI/ML data use cases is advantageous.

Design and deliver scalable Generative AI solutions using LLMs, RAG, AI agents, vector databases, and multimodal models. Lead cloud, MLOps, security, governance, and architecture strategies across AWS, Azure, and Google Cloud. Translate business needs into technical solutions, support client workshops and pre-sales, present strategies to executives, and mentor data science, ML engineering, and software teams.

Leads global people reporting, metrics governance, data quality, semantic modeling, and HR-Finance reconciliation. Owns executive reporting, self-service analytics, report rationalization, privacy controls, lineage, and historical workforce data integrity. Partners with HRIS, IT, Finance, Analytics, and AI teams while leading distributed teams and establishing enterprise standards for governed people data.

Develop and maintain industrial desktop software using C# and .NET, including user interfaces, business logic, databases, APIs, dashboards, and data visualization. Integrate applications with PLC-driven systems, industrial data platforms, and engineering workflows. Troubleshoot software and database issues, participate in testing and code reviews, document solutions, and collaborate with multidisciplinary engineering teams on modernization and digitalization initiatives.

Provide production support for critical banking technology infrastructure, rapidly resolve incidents, participate in major incident management, and improve application-support efficiency. The role involves Linux/Unix administration, Java and database technologies, middleware, microservices, containers, cloud platforms, monitoring, scheduling, CI/CD, and messaging tools. Responsibilities also include stakeholder communication, risk and control management, technical issue resolution, operational support during shifts and releases, and occasional weekend coverage.

Design, develop, test, debug, and support a microservice-based SaaS platform in Azure. Build and deploy NestJS microservices on Kubernetes, write unit tests using TDD, contribute to architecture and technical standards, collaborate in an Agile environment, refine and estimate user stories, and provide technical platform support. The role also involves optimizing SQL and NoSQL databases and configuring Auth0 and API gateway integrations.

Leads data science teams supporting commercial healthcare analytics, translating business needs into analytical problems and production-grade ML and GenAI solutions. Responsibilities include defining technical requirements, developing models, applying GenAI, managing end-to-end projects, collaborating with stakeholders, presenting insights to executives, mentoring data scientists, and building expertise in oncology analytics, patient-level data, HCP analytics, and segmentation.

Designs, develops, and supports global digital Quality Management System applications using Microsoft Power Platform. Builds Power Apps, SharePoint structures, Power Automate workflows, and integrations with ERP, data lake, and reporting systems. Translates quality and operational requirements into scalable tools supporting CAPA, 8D, audits, supplier quality, and complaints. Ensures data governance, security, and performance while supporting global deployments, training, documentation, troubleshooting, and continuous process improvement.

Supports finance and risk regulatory change initiatives as a business analyst. Responsibilities include documenting requirements, analyzing complex regulatory data models and high-volume datasets, designing functional solutions, identifying risks and trade-offs, supporting stakeholder decisions, and providing subject matter expertise. The role also involves working with Basel III/IV, PRA/COREP reporting, HSBC credit-risk data, SQL, Excel, Python, and Google Cloud Platform in complex global programs.

Own the Salesforce platform and broader integration architecture end to end. Design data models, integrations, automations, custom Apex and LWC solutions, deployments, CI/CD pipelines, and Git-based change control. Apply AI-assisted development using Claude and related tools with rigorous review, testing, and controlled releases. Lead technical delivery for developers and QA testers, manage sprint flow and debugging, translate business requirements into technical solutions, and establish platform engineering standards across the technology ecosystem.

Design and lead scalable Generative AI solutions using LLMs, RAG, AI agents, vector databases, cloud platforms, and MLOps/LLMOps. Translate business needs into secure technical architectures, conduct client workshops, support pre-sales, and present AI strategies to executives. Establish governance, security, monitoring, and compliance frameworks while mentoring data scientists, ML engineers, and software teams. Evaluate emerging technologies, guide implementation approaches, and drive enterprise AI adoption.

Design, build, test, document, and deploy cross-platform tools, frameworks, and services for large-scale product data ecosystems. Lead technical discussions, improve platform reliability and scalability, develop reusable components, optimize performance, and collaborate with engineering teams and users. The role also involves desktop application development, automated testing, CI/CD, distributed version control, and data architecture.

Owns end-to-end production data engineering for automated advertising optimization. Responsibilities include building scalable batch pipelines, managing Airflow DAGs, developing advanced SQL and feature stores, orchestrating SageMaker model training and inference, implementing data-quality gates, troubleshooting live workflows, and maintaining safe, idempotent marketplace writes. The role also translates advertising requirements into data models, collaborates with data scientists and platform teams, mentors engineers, and provides technical direction.

Extracts, transforms, and analyzes media measurement data to identify insights, test hypotheses, and answer client and stakeholder questions. Leads data investigations, develops analytical solutions, supports sales feasibility reviews, and contributes to reporting tools and automation. Collaborates across teams, formulates technical approaches to open-ended problems, and improves analytical workflows using SQL, Python or R, ETL tools, cloud technologies, and Excel.

Designs, develops, and maintains automated UI and API test solutions using Selenium, Playwright, and Tosca. Builds automation frameworks, integrates test suites with Jenkins CI/CD pipelines, validates backend data with SQL, analyzes failures, reports defects, and performs root cause analysis. Collaborates in Agile/Scrum ceremonies while improving test stability, coverage, and quality engineering practices.

Execute functional, regression, integration, API, and UAT testing for Salesforce applications across Sales Cloud, Service Cloud, and CPQ. Design test cases, validate end-to-end business processes, document results, track defects, and improve QA processes within Agile/Scrum teams. The role may also support automation, ERP integration, database, ETL, and Salesforce platform testing.

Analyze and improve data quality, lineage, controls, and authoritative sources. Build data pipelines, logical data models, dashboards, reports, and automated analytics. Apply statistical, machine learning, and advanced analytical techniques to identify trends, risks, anomalies, and improvement opportunities. Translate complex findings into actionable recommendations for senior stakeholders while ensuring data governance, privacy, security, regulatory compliance, and reporting accuracy. Partner across business, technology, risk, finance, operations, and data teams, potentially leading analytical workstreams.

Designs and develops scalable data management solutions, including data acquisition, integration, transformation pipelines, data structures, and cloud or edge infrastructure. Uses Azure Data Factory, ADLS, Databricks, SAP Data Services, DevOps pipelines, and containerization. Collaborates with analysts, architects, product owners, and technical leads to define requirements, deliver high-quality code, and support application enhancements.

Build and maintain secure, scalable data pipelines, warehouses, and lakes. Design distributed processing architectures using AWS and Hadoop technologies, develop ETL and analytical solutions, and collaborate with data scientists on machine learning deployment. The role also involves technical design, advanced SQL and programming, stakeholder partnership, risk management, and potentially leading and developing a team.

Develops and maintains OBIEE/OAS dashboards, analyses, BI Publisher reports, and RPD metadata models. Designs subject areas and logical table sources, implements row-level security, develops ODI ETL solutions, and performs query optimization, cache management, and performance tuning. Supports production issues, enhancements, and migrations while using SQL, PL/SQL, data warehousing, Unix/Linux, shell scripting, and version control.

Leads enterprise data management, modernization, governance, and AI transformation initiatives. The role architects scalable cloud data platforms and AI-ready data products, including GenAI and agentic AI solutions using LLMs, RAG, vector databases, knowledge graphs, and semantic layers. Responsibilities include executive client engagement, consulting, solution architecture, program and team leadership, delivery governance, financial performance, pre-sales, account growth, and mentoring senior data and AI professionals.