Top SQL Jobs in Pune

The Senior Business Financial Analyst transforms financial data into business insights, supporting strategic decisions and performance analysis while partnering with various teams for financial reporting and forecasting.

Owns service management and production readiness for mission-critical payment, data, and platform services. Leads incident and problem management, root cause analysis, change and release governance, certificate lifecycle management, risk and compliance controls, service monitoring, and continual improvement. Partners with engineering, product, operations, customer support, risk, and external stakeholders to improve resilience, reliability, customer experience, and operational outcomes across distributed environments.

Design, develop, and optimize scalable ETL/ELT pipelines using Databricks, PySpark, SQL, GCP, BigQuery, and Delta Lake. Build agentic workflows that automate data validation, troubleshooting, and operational processes. Develop reusable frameworks, implement data quality and monitoring controls, optimize workloads, and support testing, deployment, productionization, and ongoing enhancements across data and AI-enabled solutions.

Designs, develops, and maintains data solutions, pipelines, and ETL processes using Snowflake. Ensures data quality, supports data migration across systems, applies data modeling and governance practices, and collaborates with multiple teams. The role serves as a subject matter expert, makes team decisions, solves cross-team data problems, and mentors junior data engineers.

Design, develop, and maintain data solutions, pipelines, and ETL processes across systems. Ensure data quality, support data modeling and governance, and collaborate with multiple teams on data requirements and technical decisions. Serve as a subject matter expert, manage team activities, mentor junior engineers, and provide solutions to cross-team data engineering challenges.

Design, develop, and maintain data solutions, pipelines, and ETL processes using Snowflake. Ensure data quality, support data migration across systems, and apply data modeling, querying, and governance practices. Collaborate with multiple teams, make technical decisions, provide solutions, and mentor junior data engineers. The role requires at least five years of Snowflake experience and 15 years of full-time education.

Designs and maintains scalable data pipelines using AWS, Spark, Kafka, Airflow, and related technologies. Collaborates with product, data science, and business teams; develops reporting dashboards; documents data flows and runbooks; optimizes workflows; troubleshoots data processing issues; and supports Agile delivery and CI/CD practices.

Own the Ocean reporting portfolio, roadmap, governance, prioritization, and delivery outcomes. Lead and coach reporting professionals, manage stakeholders and dependencies, and ensure reporting quality and adoption. Develop advanced Power BI dashboards, semantic models, Excel solutions, SQL queries, and Python automations. Use Databricks, Dremio, Power Automate, and AI-enabled solutions to improve scalability, efficiency, validation, and self-service reporting.

Designs, develops, and supports complex Oracle Integration Cloud integrations using Oracle, Salesforce, REST, SOAP, database, and file-based adapters. Creates integration architecture, technical documentation, transformations, APIs, security configurations, error handling, and automated data processes. Develops VBCS and PCS extensions, performs testing and deployments across environments, supports go-live and production operations, troubleshoots integration failures, conducts root-cause analysis, and tunes performance.

Develop Oracle Integration Cloud integrations with Oracle Fusion using adapters, mappings, FBDI, REST APIs, and fault handling. Build BI Publisher reports with SQL data models, RTF or Excel templates, scheduling, and bursting. Support OTBI and potentially VBCS screen development. Work directly with clients and integrate Fusion with Model N across pricing, contracts, rebates, chargebacks, and customer and product master data.

Designs and oversees scalable GCP cloud architectures and data platforms. Builds Python-based ETL/ELT pipelines using BigQuery, Cloud Functions, Cloud Run, Composer, Dataform, Pub/Sub, and Eventarc. Integrates external APIs, automates CI/CD, optimizes data processing costs, and ensures security, governance, and compliance. The role also collaborates with stakeholders, guides other architects, manages solution governance, and translates business requirements into maintainable data engineering solutions.

Leads major incident response, L3 application escalations, root-cause analysis, reliability engineering, change risk assessment, disaster recovery validation, and observability improvements. Builds automation and recovery frameworks using scripting, tunes Java and .NET applications, validates operational readiness, and mentors support teams. The role requires strong application architecture, distributed systems, middleware, database, monitoring, and production operations expertise in regulated environments, with on-call support and hybrid work.

Own advertising performance for a portfolio of marketplace accounts across strategy, targets, partner relationships, and outcomes. Manage Amazon Ads, Amazon DSP, and Amazon Marketing Cloud campaigns; translate data into commercial decisions; proactively identify risks and optimization opportunities; lead partner conversations; manage budgets; and support team targets. The role also includes mentoring or line management, performance reporting narratives, and autonomous account ownership.

Designs and develops cloud-based data engineering solutions on GCP. Responsibilities include building data pipelines and warehouse solutions using Python, SQL, BigQuery, Dataform, Cloud Composer, Pub/Sub, and related GCP services. The role also involves applying data modeling, CI/CD, Git workflows, problem-solving, requirements gathering, client interaction, and potentially technical team management.

Develop and deliver scalable, secure software and infrastructure solutions for banking applications. Responsibilities include Java and Spring development, API and messaging integration, cloud architecture, CI/CD, infrastructure as code, container orchestration, blockchain-related systems, testing, code reviews, risk controls, and cross-functional collaboration. The role also involves guiding team members, influencing stakeholders, and supporting technology strategy and operational excellence.

Leads enterprise analytics and BI initiatives by architecting Power BI dashboards, standardizing KPIs, automating reporting, and analyzing complex datasets. Builds and deploys machine learning and generative AI solutions for forecasting, financial reporting, document insights, and chatbot support. Partners with finance, data engineering, and cross-functional teams to improve data governance, deliver strategic insights, mentor analysts, and promote data literacy.

Provides high-touch subscriber support while translating customer feedback into product improvements. Responsibilities include managing support tickets, resolving payment and account issues through Stripe, analyzing support trends, prioritizing the product backlog, writing requirements and user stories, coordinating feature launches, training support teams, and reporting customer and product KPIs to leadership.

Designs and executes manual and automated tests for Java-based, message-driven supply chain systems. The role validates asynchronous workflows, data replication, APIs, integrations, and cross-system consistency; maintains regression suites and production-like test environments; analyzes data discrepancies; and manages defects through resolution. Requires backend and integration testing experience, SQL proficiency, API testing, middleware validation, version control, UI automation, and familiarity with ElectronJS.

Conduct quantitative alpha research for systematic equity strategies, including data collection, analysis, back-testing, implementation, and model ensemble. Research portfolio optimization, transaction costs, and risk models; maintain research and production infrastructure; and support portfolio managers with risk monitoring, performance attribution, transaction-cost analysis, and investment presentations.

Build and maintain a canonical customer operating data layer integrating Salesforce, Jira, Langfuse, Snowflake, product telemetry, and other sources. Develop data models, integrations, reconciliation logic, automation, alerts, executive reporting, and AI-supported customer summaries. Translate lifecycle requirements into reliable workflows and production-ready code while partnering with business, technical, BI, and source-system stakeholders. Establish data governance, metric definitions, freshness standards, and reporting consistency for customer health, adoption, renewal, and expansion decisions.

Manages enterprise monitoring and observability platforms, provides third-line service operations support, oversees capacity and performance, develops automation, maintains support documentation, and supports business continuity and disaster recovery. The role administers Microsoft Azure, Active Directory, SQL backup solutions, Azure Analytics, KQL, monitoring integrations, and end-user monitoring solutions. It also participates in change forums and an out-of-hours support rota.

Develop and support Oracle Cloud integrations using OIC, including REST/SOAP, file-based, and event-driven workflows. Build BIP data models, templates, OTBI reports, bursting definitions, and automated extracts. Develop VBCS applications, document technical designs, conduct testing and code reviews, troubleshoot production incidents, optimize performance, and manage Oracle Support requests. The role requires Oracle SaaS knowledge, SQL/PL-SQL, web services, authentication, and front-end development skills.

Build and improve infrastructure supporting GPU firmware development, including build systems, regression farms, CI/CD pipelines, developer tools, test frameworks, web services, release pipelines, and observability. Debug issues across hardware, software, and processes; create AI-powered workflows; automate toil; and develop scalable internal tooling. Collaborate closely with hardware and software engineers while documenting requirements, designs, and trade-offs.

Build and operate production-grade AI applications, agents, data products, pipelines, APIs, and intelligent workflows. Responsibilities include agent orchestration, retrieval, model integration, cloud and platform engineering, CI/CD, security, observability, evaluation, and production validation. The role requires developing scalable enterprise AI systems using Python and SQL, integrating models and business systems, and assessing data, retrieval, model, and agent quality.

Develop high-performance Java and Spring Boot backend applications and deploy cloud-native systems on Azure. Design microservices, maintain CI/CD pipelines, support Docker and Kubernetes deployments, and contribute to infrastructure automation using Terraform and Helm. Collaborate with product owners and cross-functional teams to deliver reliable, low-latency solutions. The role requires strong Java, SQL, Hibernate, Linux, cloud, and DevOps skills, with office work required three days weekly.