Top SQL Jobs in Pune

Leads customer-embedded AI discovery and rapid proof-of-concept development for issuer and acquirer clients. Builds agentic pipelines, conversational interfaces, and analytical tools to validate business hypotheses, gathers customer feedback, and translates findings into evidence-backed product briefs and roadmap recommendations. Partners with product and engineering teams, identifies repeatable platform opportunities, supports pre-sales discussions, and mentors engineers and analysts on customer discovery and PoC scoping.

Leads software engineering efforts supporting billing operations and business systems. Designs, integrates, tests, and supports billing platforms, APIs, microservices, SaaS, ERP, CRM, ETL, and database-driven systems. Applies strong programming, SQL, data modeling, automation, security, and DevOps practices while partnering with finance, product, operations, customer success, and engineering stakeholders. Mentors team members, improves processes, translates business requirements into technical outcomes, and ensures accurate invoicing, reconciliation, reporting, and system quality.

Owns platform product vision, roadmap, feature prioritization, requirements, releases, metrics, operational health, and customer-impacting issues. Partners with engineering, UX, technical program managers, business stakeholders, vendors, and customer service. Drives platform launches, documentation, PCI audits, vulnerability and technical-debt tracking, performance analysis, and continuous improvements while mentoring team members.

Leads multiple software engineering teams developing secure, scalable ecommerce payment authentication solutions. Oversees strategy, staffing, budgets, processes, project delivery, quality, compliance, and technical direction. Requires extensive software engineering leadership and EMVCo 3DS payments experience, with strong expertise in Java, Spring, cloud platforms, microservices, security, and modern development practices. Partners across global technology, business, and external provider teams while mentoring staff and driving continuous improvement.

Build and improve production-oriented enterprise AI solutions using prompts, LLMs, RAG, workflow automation, APIs, governed data, and evaluation frameworks. Integrate systems such as Salesforce, Slack, Snowflake, and AWS using n8n, Python, JavaScript, or TypeScript. Apply context engineering, observability, security, privacy, testing, and reliability controls while partnering with business, product, data, security, and engineering stakeholders.

Leads enterprise data quality strategy, architecture, platforms, frameworks, observability, governance, and automation. Designs reusable quality capabilities for batch, streaming, cloud, on-premises, and SaaS environments; establishes rules, metrics, alerts, and remediation workflows; integrates quality with metadata, lineage, catalogs, MDM, and data contracts; mentors engineering teams; evaluates tools; and applies AI and machine learning to anomaly detection, root-cause analysis, and trusted AI-ready data platforms.

Design and develop a scalable automated locates platform for securities finance using Java, Spring, microservices, distributed systems, containers, AWS, SQL, caching, and messaging technologies. Build enterprise applications, optimize transactional data models and queries, integrate with existing workflows, and collaborate with developers, analysts, QA, and operations teams.

Leads the design, development, deployment, and support of scalable data pipelines and platforms across Hadoop, on-premises, and AWS cloud environments. Builds batch and near-real-time processing frameworks, modernizes ETL and data warehouse workloads, implements governance and observability capabilities, and troubleshoots production issues. Mentors engineers, collaborates with cross-functional stakeholders, evaluates emerging technologies, and ensures secure, high-quality delivery for enterprise-scale data ecosystems.

Build and maintain petabyte-scale data pipelines, entity-centric data models, and distributed workflows using Databricks and Spark. Partner with data science teams to productionize ML features and artifacts, optimize ETL/ELT processes, and implement testing, monitoring, observability, and incident response. Collaborate with governance and operations teams to ensure secure, compliant data management while supporting scalable merchant identity and trust-profile systems.

Build and enhance Ethoca products across the full software development lifecycle, including design, development, testing, deployment, configuration, and documentation. Develop scalable test automation frameworks, review quality solutions, promote shift-left practices, and contribute to architecture and design decisions. Collaborate with product and engineering teams, manage risks, integrate services, mentor engineers, and improve operational metrics. Work with microservices, distributed systems, cloud-native applications, APIs, CI/CD platforms, and data validation.

Build and operate production LLM systems, including prompt and pipeline versioning, evaluations, monitoring, observability, RAG and vector-store infrastructure, safety guardrails, and cost governance. Develop CI/CD and operational tooling for non-deterministic AI outputs, manage reliability and compliance requirements, and collaborate with engineering and product teams to turn AI prototypes into scalable, secure, cost-effective production systems.

Develop and maintain Alteryx automation workflows for data preparation, reconciliation, reporting, validation, and exception management. Design preventive and detective controls, document data lineage, investigate data-quality issues, and support testing, releases, production implementation, and remediation. Collaborate with technology, operations, risk, control owners, and data stakeholders to standardize processes, improve efficiency, and strengthen control effectiveness.

Own delivery of shared data models and pipelines, lead migration from Hadoop and on-premises ETL to Databricks, manage cross-team dependencies, oversee vendors, maintain legacy platform commitments, and establish planning and reporting practices for a new technical team.

Owns the vision, roadmap, backlog, requirements, and launches for data platform products. Translates business and customer needs into technical features, user stories, and acceptance criteria; partners with engineering and technical program teams; monitors product performance, adoption, and operational health; manages documentation, prioritization, and post-launch feedback. The role also supports data quality, governance, analytics, stakeholder collaboration, mentoring, and hiring activities.

Leads the design and development of scalable Java backend applications using Spring Boot, microservices, and REST APIs. Provides architectural and technical leadership, mentors engineers, drives coding standards, and oversees initiatives from design through production support. Collaborates with product, architecture, QA, DevOps, and engineering teams while resolving complex technical issues and performance bottlenecks. Preferred experience includes payments or fintech, Kafka, databases, cloud platforms, Kubernetes, security, CI/CD, and mobile application backends.

Design and develop a scalable automated securities finance platform using Java, Spring, microservices, distributed systems, containers, SQL, AWS, messaging, and caching technologies. Build enterprise applications, optimize high-volume transactional data models and queries, integrate with existing workflows, and collaborate with developers, analysts, QA, and operations teams.

Lead Software Engineer responsible for developing, maintaining, and supporting high-availability payment platforms. The role involves Java backend development, Oracle database work, REST and event-driven integrations, production reliability, Agile delivery within SAFe, distributed team collaboration, testing, automation, and continuous improvement. Experience with Spring Boot, Angular, JavaScript, SQL, DevOps tools, and security mechanisms is required; payment or financial-services experience is preferred.

Lead the architecture and development of scalable batch, streaming, and event-driven data platforms supporting analytics, machine learning, generative AI, and agentic AI. Build governed lakehouse architectures, reusable data products, ingestion and orchestration pipelines, and AI lifecycle capabilities. Drive security, governance, observability, reliability, performance, and cost optimization while translating R&D concepts into production systems. Provide hands-on technical leadership, architecture reviews, mentorship, and cross-functional collaboration.

Lead the architecture and hands-on development of scalable batch, streaming, and event-driven data platforms supporting analytics, machine learning, generative AI, and agentic AI. Build governed lakehouse architectures, reusable data products, ingestion and orchestration pipelines, and ML lifecycle capabilities. Establish standards for security, governance, testing, CI/CD, observability, reliability, and cost optimization while providing technical leadership, mentoring, architecture reviews, and cross-functional collaboration.

Leads the architecture, development, and productionization of AI/ML and GenAI solutions for healthcare operations. Responsibilities include building clinical and claims data pipelines, developing LLM and RAG applications, implementing MLOps and LLMOps, ensuring HIPAA-compliant governance, translating business needs into technical roadmaps, communicating with stakeholders, and mentoring engineers.

Supports APJ territory planning, Salesforce deployment, account routing, reporting, data hygiene, process documentation, and automation improvements. Partners with Field Sales, Sales Operations, Revenue Strategy, and Sales Systems while responding to routing questions and maintaining accurate account data. This early-career role requires Salesforce familiarity, spreadsheet skills, attention to detail, and clear asynchronous communication. Prior territory operations experience is not required.

Leads client-facing data engineering engagements from discovery through production, translating business requirements into cloud architectures, ETL/ELT pipelines, data lakes, warehouses, and analytics solutions. Oversees technical delivery, project planning, quality reviews, testing, documentation, and stakeholder communications. Mentors engineers and consultants, drives coding and data quality standards, supports business development, and develops scalable solutions using Python, SQL, Spark, and major cloud platforms. The role also contributes to AI-enabled data engineering and supply chain or manufacturing solutions.

Develops and maintains high-quality software using modern engineering practices and contributes as a senior technical expert. The role includes leading technical efforts, resolving blockers, coaching junior developers, reviewing and approving code, supporting architecture and performance decisions, collaborating with Product Owners in Agile/Scrum teams, and working with React, .NET, Azure, SQL, CI pipelines, and distributed teams.

Design, develop, and improve scalable automation software and platform capabilities. Collaborate across teams to define requirements, implement secure coding and unit testing, deploy with containerization and cloud platforms, manage automation tool incidents via ITIL processes, and build monitoring/observability and reporting solutions to support Location Strategy projects.

Manage and administer CPM/EPM and financial systems supporting planning, budgeting, forecasting, consolidation, and reporting. Configure dimensions, hierarchies, workflows, metadata, security, integrations, and business rules; monitor performance and resolve complex issues. Partner with Finance, IT, vendors, and stakeholders on requirements, reporting, testing, releases, enhancements, and finance transformation initiatives. Provide user support, training, governance, documentation, data analysis, and continuous process improvements.