Top SQL Jobs in Pune

Own the revenue operations engine across CRM architecture, pipeline reporting, forecasting, funnel optimization, GTM automation, and market intelligence. Build automated enrichment, scoring, and outreach workflows; integrate CRM and engagement systems; segment private equity accounts; map buying committees; and translate market signals into prospecting, messaging, and sales plays.

Own and govern company-wide SaaS metrics including ARR, ACV, NDR, GDR, and customer counts. Define and certify metric standards, reconcile inconsistencies across Salesforce, NetSuite, customer success, and product systems, establish data quality and lineage controls, and partner with BI, data engineering, and business stakeholders to automate reporting and maintain a trusted source of truth.

Leads a 3–6-person AI-focused engineering team while contributing at least 50% directly to software development. Responsibilities include architecture, full-stack coding, code reviews, testing, documentation, mentoring, delivery, and collaboration with product, design, and QA teams. The role requires commercial LLM experience, strong C# and JavaScript development skills, knowledge of databases, REST APIs, microservices, cloud platforms, and software engineering management.

Leads multi-touch attribution engagements for pharmaceutical and biotech clients, integrating commercial data and designing attribution models to measure HCP and patient touchpoint impact on prescriptions. Translates analytical outputs into executive recommendations on channel ROI and budget allocation, validates models, ensures regulatory compliance, and manages a team of consultants and analysts. Responsibilities also include client engagement leadership, methodology development, thought leadership, and proposal support.

Develop software and data warehousing solutions supporting fraud detection and identity proofing. The role involves Java, Python, SQL, Snowflake, Yugabyte, ETL/ELT, cloud deployment, containerization, continuous integration, automated deployments, event-based systems, and structured and unstructured data stores. Responsibilities support AWS-based customer protection technology and may involve Docker, Kubernetes, Jenkins, Kafka, Terraform, and related data platforms.

Evaluates and compares AI chatbot responses using predefined criteria for accuracy, relevance, completeness, clarity, and quality. Documents findings, analyzes business requirements, maps processes, identifies response-quality issues, prepares reports, and collaborates with project teams. The role is a fully remote, full-time 16-week contract requiring five days per week, possible weekend work, and at least four hours of overlap with US Pacific Time.

Evaluates AI-generated data science and quantitative reasoning outputs; develops prompts, datasets, reference solutions, and objective evaluation benchmarks. Identifies statistical errors, flawed methodologies, and unsupported conclusions while providing structured feedback to improve model accuracy. Responsibilities include dataset validation, statistical and quantitative assessment, quality assurance, technical documentation, and clear communication of analytical findings.

Principal Full Stack Engineer responsible for setting technical direction while remaining deeply hands-on across Laravel, PHP, Next.js, AWS, and GCP. The role owns platform architecture, leads cross-team technical initiatives, improves testing, CI/CD, observability, and scalability, and mentors engineers through influence. Responsibilities also include evaluating AI technologies, supporting event-driven and modular architectures, guiding roadmap trade-offs, and solving complex system-level challenges across product squads.

Design and maintain ETL/ELT pipelines and data warehouse architecture, analyze and visualize data with SQL/Python/R and BI tools, build machine learning models and A/B tests, and partner with engineering and business teams to deliver data-driven insights for fintech use cases (fraud detection, segmentation, forecasting).

Build and operate cloud-native backend services in Go. Responsibilities include designing RESTful APIs and microservices, writing reliable and secure code, monitoring production systems, participating in on-call rotations, troubleshooting infrastructure and integrations, and improving scalability and performance. The role requires collaboration within an agile team and familiarity with databases, AWS, containers, orchestration, and CI/CD tools.

Leads MetLife’s India-based enterprise data engineering organization, overseeing data architects, engineers, platform engineers, and scrum leads. Responsibilities include setting data engineering roadmaps, designing scalable data architectures and platforms, directing ETL/ELT solutions, improving data governance and storage, and delivering trusted data products. The role also owns talent acquisition, team development, cultural transformation, stakeholder alignment, and strategic data-driven innovation across global financial services operations.

Leads major incident response, L3 escalations, technical root-cause analysis, and long-term remediation for production applications. Applies SRE practices, tunes Java and .NET runtimes, validates disaster recovery, assesses high-risk changes, and improves reliability through automation, monitoring, and observability. Mentors support teams, approves operational documentation, and advises stakeholders in regulated production environments. Requires on-call availability and strong expertise across application architecture, middleware, infrastructure, scripting, databases, and performance engineering.

Leads the design, development, testing, deployment, and support of enterprise-scale full-stack applications. Provides technical leadership on architecture, Java and Spring Boot development, APIs, microservices, event-driven systems, cloud-native platforms, DevSecOps, CI/CD, automated testing, and production stability. Collaborates with product, architecture, and business stakeholders, supports Agile delivery, manages technical risk, and mentors engineers while promoting engineering standards and continuous improvement.

Lead the strategy, architecture, and evolution of enterprise data platforms supporting secure data exchange, discovery, governance, integration, and self-service consumption. Establish scalable patterns for data quality, lineage, observability, privacy, and security while reducing bespoke workflows through automation. Provide technical leadership across engineering organizations, influence architecture decisions, mentor technical teams, and translate complex business needs into reusable cloud and on-premises data solutions.

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 high-performance enterprise applications, optimize transactional data models and queries, integrate real-time processing systems, and collaborate with development, business analysis, QA, and operations teams.

Build and administer enterprise QlikView and Qlik Sense platforms, develop dashboards and data models, and integrate analytics with Snowflake, AWS S3, and multiple databases. Responsibilities include platform upgrades, security, monitoring, troubleshooting, incident management, data ingestion, ETL, service governance, and stakeholder coordination. The role supports global BI users, drives automation and continuous improvement, and requires strong infrastructure, SQL, DevOps, and ITIL knowledge.

Designs and executes UI performance, API, and end-to-end automated tests using Playwright or Selenium, Artillery, JavaScript or Java, SQL, and CI/CD pipelines. Analyzes test results, debugs failures, performs root cause analysis, validates data, and collaborates with development and product teams to improve quality. The role also tests AI-driven features and uses AI coding tools. Preferred experience includes cloud technologies, Datadog, Jenkins, Allure, Docker, and permission testing.

Designs, develops, and deploys autonomous and multi-agent AI systems for business workflows. Builds agentic applications using LLMs, RAG, vector databases, tool calling, memory, and orchestration frameworks. Integrates agents with enterprise applications, APIs, databases, CRMs, and ERPs while developing backend services and APIs. Optimizes solutions for scalability, security, performance, and cost, and collaborates with product, engineering, and business teams to identify automation opportunities.

Build and deploy agentic finance AI solutions: design voice‑optimized prompts and conversational flows, integrate LLMs (Gemini/GPT/Claude) with RAG and enterprise data, implement voice/speech/telephony integrations, automate workflows and reporting using Python and SQL, and collaborate across product, engineering, and operations to tune and monitor production ML systems.

Analyze operational data and processes, identify bottlenecks, design scalable solutions, automate workflows and reporting with Python and SQL, build dashboards and monitoring, perform root-cause analysis, document logic and collaborate with product, engineering, and ops teams to improve automation and data quality.

Leads global workforce analytics and reporting, translating HR data into actionable insights for business leaders. Responsibilities include dashboard development, headcount reporting, forecasting, data quality management, governance, dimensional data modeling, advanced SQL analysis, and collaboration with HR systems, engineering, and FP&A teams. The role also explores Generative AI to automate reporting and enhance employee analytics.

Leads full-stack software engineering efforts, including application design, coding, API development, performance optimization, testing, debugging, code reviews, and architectural decisions. Owns CI/CD pipelines and infrastructure-as-code strategies, evaluates technologies, improves code quality and scalability, and collaborates with product, design, services, and DevOps teams. Develops secure applications handling protected health information in accordance with HIPAA standards.

Owns application management for banking applications, ensuring security, risk, compliance, audit, lifecycle, access, monitoring, disaster recovery, capacity, infrastructure, and upgrade requirements are met. Coordinates remediation, incident management, stakeholder and vendor activities, and application events. Requires basic technical and infrastructure knowledge, understanding of information security controls, IAM, governance, compliance, audit processes, and systems development lifecycle practices.

Develop and maintain Python and Appium automation frameworks for Android and iOS applications. Perform functional, regression, integration, UI, and API testing; execute test suites, investigate failures, and manage defects in JIRA. Integrate automation with CI/CD pipelines, maintain test documentation, and collaborate with engineering and product teams. Experience with Selenium, BDD, cloud testing, SQL, Docker, and AEC or construction technology is advantageous.

Design and optimize scalable ETL/ELT pipelines and modern data platforms using Databricks, PySpark, Azure Data Factory, ADLS, Delta Lake, and Synapse Analytics. Develop data ingestion and transformation workflows, optimize Spark performance, implement CI/CD automation, and uphold data quality, security, and governance standards. Collaborate with architects, analysts, and business stakeholders on cloud-based data engineering solutions.