Top SQL Jobs in Pune

Lead bank liquidity risk reporting and management by developing funding strategies, monitoring liquidity metrics, assessing regulatory and behavioral impacts, managing intra-group funding, and designing stress-testing methodologies. The role advises senior stakeholders, ensures regulatory and governance compliance, drives automation and analytical improvements, and develops tools to strengthen liquidity resilience and decision-making.

Develops and delivers software features while meeting quality and performance standards. Responsibilities include requirements analysis, coding, unit testing, documentation, debugging, release processes, client and partner communication, training, knowledge sharing, and platform improvement. Works under the guidance of senior team members and creates solutions tailored to customer needs.

Leads Oncology commercial analytics and brand strategy insights across inline and pipeline assets. Translates business priorities into analytical plans, oversees patient journey and real-world data modeling, supports precision medicine and biomarker initiatives, and applies statistical, machine learning, and AI methods. Manages 15+ team members and cross-functional insights pods while partnering with global, regional, marketing, clinical, medical affairs, and business development stakeholders. Drives scalable analytics, GenAI experimentation, prioritization, value tracking, and executive decision-making.

Develop and maintain Java backend services, APIs, database integrations, and cloud-native solutions. Responsibilities include system design, performance optimization, secure coding, testing, CI/CD, code reviews, production troubleshooting, root-cause analysis, and collaboration with cross-functional teams. The role also involves mentoring junior developers and contributing to scalable enterprise supply chain software, with exposure to cloud platforms, integration protocols, frontend technologies, and emerging AI-driven engineering practices.

Develops and delivers software features according to quality and performance standards. Responsibilities include requirements analysis, coding, unit testing, documentation, troubleshooting, release processes, client communication, training, knowledge sharing, and platform improvement. Works under the guidance of senior team members and supports customer-specific configurations.

Build and maintain cloud data architectures, pipelines, warehouses, and lakes that securely process large-scale data. Develop data-processing and analysis algorithms, support container platforms, and collaborate with data scientists to deploy machine-learning models. The role requires AWS, Databricks, distributed computing, Hadoop, SQL, shell scripting, and Python expertise. Responsibilities also include operational excellence, risk and controls, stakeholder collaboration, problem-solving, and potentially leading and developing team members.

Provide Level 2 production support for financial crime applications, ensuring availability, performance, scalability, and resilience. Respond to incidents, participate in major incident management, perform root-cause analysis, automate operational processes, tune systems, and improve support efficiency. Collaborate with development, infrastructure, compliance, and business teams while communicating with senior stakeholders. The role includes shift-based and occasional weekend support, release activities, monitoring, capacity planning, and implementing preventative measures for recurring incidents.

Leads software and platform engineering for warehouse automation systems. Designs Java applications, Kafka-based event-driven integrations, APIs, and containerized deployments while improving scalability, reliability, observability, and DevSecOps practices. Partners with architects, SREs, and operational technology teams to evolve warehouse control platforms, integrate robotics and PLC-based systems, mentor engineers, define technical roadmaps, and support implementation and commissioning activities.

Build ETL pipelines, data crawlers, warehouse models, and optimized SQL processing scripts for Decision Intelligent applications. Analyze complex use cases, troubleshoot skill lifecycles, document technical solutions, and collaborate with Solution Architects. The role requires BI, data warehousing, columnar database, API, and prompt engineering expertise, plus experience in Agile/Scrum environments and operational controls.

Designs and supports enterprise analytics experiences using Power BI, ThoughtSpot, Tableau, and Databricks. Responsibilities include developing dashboards, semantic models, KPIs, reporting standards, self-service analytics, and AI-enabled insights. Partners with data engineers and business stakeholders to translate requirements into scalable visual solutions, ensure governance and performance, support platform modernization and migrations, and promote analytics adoption through documentation and enablement.

Owns end-to-end technical solution architecture and delivery for cloud-based data projects. Designs data warehouses, data marts, databases, ETL pipelines, and technical solutions primarily on Azure. Translates business requirements into technical designs and development work, leads implementation teams, reviews code, supports testing, governs architecture standards, performs proofs of concept, and collaborates with clients, project managers, analysts, DBAs, data scientists, and global teams. Manages one to two projects and provides technical coaching and post-delivery support.

Provides first-line monitoring and support for client applications and infrastructure. Responsibilities include investigating and resolving low-complexity incidents, fulfilling service requests, performing approved patching and configuration changes, supporting clients through phone or chat, maintaining knowledge articles, improving processes through automation, and assisting with disaster recovery testing and project work.

Designs and maintains data foundations, pipelines, and end-to-end data solutions. Implements ETL and ELT processes, data integration, ingestion, modeling, processing, and quality controls across cloud platforms. Partners with technical and business stakeholders, presents findings, leads data foundation initiatives, manages operational processes, drives implementation efficiency, and mentors junior engineers.

Designs, develops, and maintains enterprise data solutions, pipelines, data foundations, and ETL/ELT processes. Ensures data quality, integrates and migrates data across cloud systems, and supports data modeling and processing. The role partners with technical and business stakeholders, leads data strategy implementation, coordinates change and incident management, presents findings, mentors junior engineers, and drives scalable, cost-effective delivery.

Designs, develops, and maintains data foundations, pipelines, integrations, and ETL/ELT solutions. Ensures data quality, supports data migration and deployment across systems, and drives implementation efficiency. Acts as a subject matter expert, mentors junior engineers, collaborates with technical and business stakeholders, supports change and incident management, and advances data strategy initiatives.

Design, develop, and maintain Snowflake-based data warehousing solutions, databases, pipelines, and ETL processes. Collaborate with data and business intelligence analysts to address data requirements, implement security and access controls, and deliver scalable applications. The role requires hands-on experience with Snowflake Streams, Tasks, Snowpipe, stored procedures, complex SQL, and Python, with AWS services as an advantage.

Build and maintain scalable backend payment services using Java, Kotlin, and Python. Develop end-to-end payment flows, including charges, refunds, disputes, and webhooks; refactor legacy services; improve testing and APIs; resolve production incidents; and reduce technical debt. Collaborate across engineering and product teams through design, code reviews, and Agile delivery. Document systems and ensure effective handoff to the full-time engineering team.

Design, build, and maintain Power BI dashboards and MI reports to monitor ITSM processes and service availability. Drive process workflow modelling, knowledge management, automation/AI initiatives, stakeholder engagement, and continual improvement to meet SLAs and quality standards.

Performs automated API and UI testing across the software development lifecycle. Develops and maintains tests using Java, JavaScript, and Python; applies BDD, Selenium, Agile, CI, integration testing, and software security practices. Creates test plans, configures testing tools, collaborates on defect resolution and build planning, and supports quality leaders and junior staff. Requires knowledge of data structures, algorithms, databases, operating systems, client-server applications, and AI-driven testing.

Develop firmware, embedded components, and Linux applications for access appliances. Responsibilities include software requirements analysis, architecture and design, feature development, debugging, testing, documentation, CI/CD support, quality collaboration, and mentoring. The role requires extensive experience with C/C++, Golang, Python, Linux system programming, REST APIs, Angular, containers, databases, and embedded build processes.

Designs, develops, tests, and improves scalable full-stack software solutions. Collaborates with product managers, designers, and engineers on requirements and integrations; participates in code reviews and technology communities; applies secure coding and DevSecOps practices; and contributes to modernization of core platforms and digital offerings. The role also involves influencing stakeholders, managing risk and controls, guiding colleagues, and supporting technology strategy. Payments-domain experience is desirable but not required.

Leads major incident response, L3 application escalations, root-cause analysis, reliability engineering, and high-risk change assessments. Tunes Java and .NET applications, validates disaster recovery, develops automation and observability frameworks, improves MTTR, and mentors support teams. Requires expertise in distributed systems, middleware, scripting, databases, monitoring tools, regulated production environments, and on-call operations.

Build and maintain system software and infrastructure for deploying, benchmarking, automating, and qualifying AI applications and models. Responsibilities include supporting inference backends, managing local model repositories, developing performance and correctness measurement systems, processing workload metrics, implementing diagnostics and observability, and maintaining automated build, integration, deployment, and qualification pipelines. The role also involves debugging system architectures, analyzing bottlenecks, and improving scalability across Linux and Windows environments.

Leads Zendesk’s AI Delivery team and customer implementations, providing technical guidance on AI product configuration, integrations, optimization, adoption, and business outcomes. Manages projects end to end, removes technical blockers, supports change management, and partners with Customer Success and Sales. Builds the delivery team, establishes methodologies, assigns work, evaluates performance, and develops team members. Uses adoption and health analytics to identify churn risks and support retention and expansion.

Leads hands-on development of scalable data engineering solutions using Python, Snowflake, Snowpark, and AWS. Designs serverless applications, stored procedures, and orchestrated DAG-based pipelines; optimizes performance and resolves production issues. Provides architectural guidance, establishes engineering standards, mentors engineers, collaborates with stakeholders, and contributes to platform modernization and technical roadmaps.