Top SQL Jobs in Hyderabad

Provide first-line product support for a B2B SaaS platform through email, chat, and calls. Troubleshoot issues, replicate bugs, coordinate escalations, track resolutions, document knowledge-base content, educate customers, monitor recurring issues, and participate in QA and beta testing. The role collaborates closely with Product, Technology, and Customer Success teams and requires Hindi proficiency.

Manage customer-related data, maintain CRM and ticketing records, generate recurring reports, track customer success KPIs, analyze feedback and support trends, and provide insights for improving engagement and service quality. The role also involves automating reporting tasks using Excel and other tools, coordinating data sharing across teams, and identifying process improvements.

Build and ship product features for government procurement and contract lifecycle software. Responsibilities include writing efficient Java code, applying data structures and algorithms, designing and managing SQL and NoSQL databases, using AI tools, debugging, testing, and owning software end to end.

Develop and deploy scalable Java applications across the full software development lifecycle. Build Spring and Spring Boot microservices, REST APIs, and AI-integrated features using OpenAI, Claude, and automation tools. Prototype frontend interfaces with Lovable, troubleshoot existing systems, collaborate with cross-functional teams, mentor junior developers, and contribute to engineering best practices.

Build and maintain Java software features under senior guidance, develop RESTful APIs and microservices with Spring and Spring Boot, integrate AI capabilities using OpenAI and Claude APIs, prototype frontend components with Lovable, debug systems, participate in code reviews, and collaborate with cross-functional teams while learning engineering best practices.

Provides Level 1 application and system support for global clients through monitoring, incident identification, troubleshooting, escalation, deployment support, dashboard creation, and operational logging. The role involves exposure to .NET, Java, databases, cloud platforms, DevOps tools, automation, and rotational shifts. Associates communicate with internal teams and clients, follow SLAs and procedures, maintain handovers, and contribute to continuous improvement.

Provides L2/L3 production support for Oracle Cloud General Ledger, resolving incidents, journal and integration issues, period-close problems, scheduled-process failures, and reconciliation discrepancies. Supports close activities, quarterly updates, testing, configuration changes, FBDI loads, Oracle Service Requests, documentation, end-user training, and SLA-based ticket management. Collaborates with AP, AR, FA, CM, and Expenses teams and participates in on-call support.

Design, build, and maintain unified data platforms using Microsoft Fabric and Azure services. Develop data pipelines, models, and analytics workloads with SQL, PySpark, and DAX. Integrate OneLake, ADLS Gen2, Synapse, Databricks, and Power BI while implementing medallion architecture, governance, lineage, CI/CD, and data-quality practices. Collaborate with stakeholders to deliver scalable solutions, troubleshoot workflows, optimize performance and costs, and meet service-level agreements.

Develop and enhance software systems using Java, Python, and .NET technologies. Build database-driven applications with SQL Server, stored procedures, functions, triggers, and complex queries. Resolve defects, create interfaces and third-party integrations, and develop reports using Crystal Reports or SSRS. Analyze business objectives, identify system improvements, and collaborate with teams while applying strong object-oriented programming, analytical, communication, and problem-solving skills.

Own end-to-end pharmaceutical market access and patient analytics modules using SQL, Python, AI/ML, and advanced analytics. Responsibilities include modeling and transforming claims, sales, and APLD data; designing dashboards; structuring analytical problems; generating actionable insights; automating recurring analyses; mentoring analysts; ensuring quality; and partnering with stakeholders to refine requirements.

Own and productionize a web data acquisition platform combining resilient crawling with AWS Bedrock-based verification. Responsibilities include modernizing HTTP and browser crawling, implementing proxy and egress management, reverse-engineering APIs, respecting robots.txt and legal requirements, containerizing and scheduling pipelines, and building testing, observability, alerting, and canary-crawl systems. The role requires deep expertise across legacy and modern scraping stacks, anti-bot reliability, data extraction, distributed crawling, compliance, and large-scale platform ownership.

Supports pharmaceutical and biotechnology client projects by integrating formulary, payer, claims, patient-level, IDN, and GPO datasets. Builds data pipelines, curated datasets, database queries, BI reports, scorecards, opportunity maps, and access analyses using SQL, Python, and visualization tools. Translates coverage and treatment-journey insights into executive summaries, recommendations, access strategies, pull-through plans, and account-planning guidance for clients.

Designs, builds, and maintains ETL/ELT pipelines, data warehouses, data models, and data quality processes. Integrates data from vendors and multiple sources, performs exploratory analysis to resolve data issues, and supports end-to-end data governance and operations. The role requires client interaction, mentoring junior engineers, and expertise in Python, PySpark, SQL, cloud platforms, Snowflake, Databricks, and pharmaceutical commercial data.

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.

Design and maintain automated tests using Python and Pytest; test REST APIs, databases, data pipelines, and Power BI dashboards. Validate data accuracy and reconciliation across source systems, APIs, databases, and reporting layers. Execute functional, regression, integration, and end-to-end testing, document defects, collaborate with development and data teams, and improve automation coverage and framework efficiency.

Early-career Associate Engineers will develop, test, debug, and maintain software and AI-first applications under experienced engineers. Responsibilities include applying programming, data structures, algorithms, SQL, APIs, Git, testing, and CI/CD practices while contributing to automation, proof-of-concepts, data, cloud, quality, full-stack, and AI/GenAI projects. The role emphasizes structured learning, collaboration, communication, problem-solving, and growth into specialized engineering disciplines.

Develop, maintain, and support AS400/iSeries applications using RPG (ILE and free-form), ACOM, and ShowCase Query. Participate in design, testing, Agile delivery, production support, change control, and SOX/IT security compliance. Collaborate with business and technical teams to estimate work, triage defects, and deploy changes to production.

Build and deploy production AI applications for enterprise Finance teams, from discovery with CFO stakeholders through prototyping, regulated deployment, adoption, and ROI measurement. Develop agentic and RAG workflows using Snowflake Cortex or Databricks Genie, LLM orchestration frameworks, vector search, and evaluation harnesses. Integrate governed enterprise data and platforms, ensure compliance and observability, and advise senior Finance leaders while creating reusable technical assets.

Develop and maintain Java Spring Boot microservices, build and consume REST APIs, write unit tests, participate in code reviews, and resolve production issues. Senior-level responsibilities include owning modules end-to-end, leading architecture discussions, mentoring junior developers, and optimizing performance. The role requires Java, Spring technologies, microservices, databases, version control, and build tools, with additional cloud, security, containerization, messaging, and CI/CD skills for senior positions.

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 AI-assisted browser automation and automated tests for web applications, APIs, and data workflows using Playwright, Stagehand, and Python. Integrate LLM APIs, CI/CD pipelines, monitoring, logging, metrics, and reporting dashboards. Develop reusable automation frameworks, evaluate deterministic versus AI-driven approaches, improve reliability, and optimize AI performance and costs.

Designs scalable Snowflake data models and architectures, builds ETL/ELT pipelines with Snowpipe, Azure Data Factory, and Matillion, and develops complex SQL and stored procedures. Responsibilities include incremental loading, data validation, performance tuning, warehouse and cost optimization, RBAC and governance, monitoring, error handling, troubleshooting, and production support. The role collaborates with cross-functional teams on requirements and solution design.

Lead the design, implementation, and optimization of Snowflake data warehousing solutions. Develop scalable data models and pipelines, optimize Snowflake performance and costs, oversee CI/CD automation, integrate monitoring and analytics tools, ensure data security and governance, and mentor junior engineers while aligning technical solutions with business requirements.

Develop and maintain Snowflake data pipelines, write and optimize SQL for integration and transformation, assist with CI/CD deployment automation, test and debug workflows, optimize performance, collaborate with senior developers, and document data processes and architectural decisions.

Design, develop, maintain, and optimize Talend ETL processes and scalable data pipelines. Extract and load data across databases, files, APIs, cloud platforms, and data warehouses such as Snowflake. Implement data transformations, quality checks, validations, monitoring, troubleshooting, documentation, governance, security, and privacy controls. Collaborate with architects, analysts, and stakeholders while supporting data migration and legacy-system integration projects.