Top SQL Jobs in Hyderabad

Design and implement scalable cloud-native data and analytics platforms (AWS/Azure) using Databricks, Snowflake, SQL, Python/PySpark. Build ingestion, ETL/ELT, orchestration, integration, and reporting pipelines. Support data modeling, analytics-ready structures, BI tools, CI/CD, deployments, production support, incident management, and AI/ML-enabled analytics. Collaborate with architects, stakeholders, and engineering teams to drive standards, governance, and operational excellence.

Lead design and delivery of NLP and Generative AI solutions, from problem definition through deployment. Build and fine-tune transformers and LLMs for summarization, QA, classification and chatbots, apply classical and deep learning methods, ensure scalable reproducible ML workflows in cloud environments, mentor junior data scientists, and collaborate with product and engineering to translate business problems into AI solutions.

Design and implement AI/LLM-driven data extraction and ETL pipelines, build web crawling and API integrations, implement RAG systems, mitigate LLM hallucinations, evaluate third-party tools, and collaborate with content and analytics teams to deliver high-quality, scalable data for downstream analysis.

Lead tax functional consultant responsible for implementing and supporting global indirect tax solutions using Vertex and Oracle Cloud Fusion Tax. Partner with business stakeholders to define processes and roadmaps, configure tax rules, manage integrations, support SIT/UAT, troubleshoot critical issues, and lead cross-functional teams through implementations and M&A-related tax integrations.

Develop, test, debug and maintain web and mobile fintech applications. Work in an Agile environment with cross-functional teams, manage time-sensitive deliverables, provide technical support, and improve user experience while reporting to IT leads and the CTO.

Design and implement Python-based automated UI and API tests using Selenium, Pytest, Rest Assured or Postman. Validate data with SQL, maintain test environments, collaborate with development and QA, analyze results, and report defects to ensure high-quality deliveries.

Deploy and productionize ML models on GCP Vertex AI for real-time and batch inference. Build scalable pipelines, perform feature engineering, monitor model performance and drift, support ML-Ops and governance, and collaborate with teams on retail banking (credit risk, marketing, customer service) use cases.

Design, build, and maintain scalable web applications using the MERN stack and Next.js. Collaborate with cross-functional teams and designers to implement UI/UX, create reusable components, optimize performance across devices, manage and improve codebases, work with SQL databases, integrate RESTful APIs, and troubleshoot complex issues.

Build Plane's outbound engine end-to-end: source and enrich lists, run multichannel cold email and LinkedIn sequences, maintain deliverability, integrate LLMs and automation, sync CRM and route leads, instrument attribution, and optimize for reply rate and pipeline.

This role involves assisting in CI/CD pipeline development, configuration management, cloud platform work, and learning DevOps tools within a remote team.

The role involves back-end development using .NET Core and SQL, contributing to Jibble 2.0 API integrations, and collaborating with product and design teams.

The Solutions Engineer will support direct sales cycles, providing technical expertise and tailored solutions for customers, while collaborating closely with Sales, Product, and Engineering teams.

Develop LookML models, Looker dashboards, and workflows for business reporting and analytics. Apply performance best practices such as caching and data modeling, manage code changes with version control, validate data using SQL Runner, and collaborate with data engineers, analysts, and stakeholders to understand requirements and deliver accurate, actionable insights.

Build and maintain end-to-end web applications using Python, modern JavaScript frameworks, and SQL databases. Develop APIs and responsive UIs, optimize database and application performance, implement testing and code reviews, manage deployments and CI/CD, monitor reliability and costs, troubleshoot production issues, and apply security and observability best practices.

Manage and support the Protiviti GRC application, including design, customization, development, testing, and production support. Coordinate with customers, technical teams, and process experts; perform quality checks; troubleshoot issues; resolve P1/P2 incidents; and identify MES automation improvements. The role also involves mentoring junior team members, supporting end-to-end MES/MOM implementations, and working rotating 24/7 shifts.

Develop predictive models and machine learning solutions using Python and data science techniques. Analyze terabyte-scale datasets, identify patterns, clean and visualize data, write SQL, and use GPUs for model development. Apply NLP, computer vision, deep learning, statistical learning, and graph-based methods. Build interpretable results in collaboration with domain experts, leaders, and engineers, and develop AI chatbots using Amazon Lex and cloud platforms.

Design and conduct advanced technical interviews and assessments for senior data science candidates. Develop current evaluation criteria, assess technical and problem-solving abilities, provide hiring recommendations, facilitate technical workshops, and mentor junior assessors. Collaborate with HR and data science teams to tailor evaluations, maintain knowledge of evolving technologies and best practices, and ensure a strong candidate experience.

Administer and support SAP Basis and HANA environments across cloud and on-premises landscapes. Responsibilities include system monitoring, performance tuning, transports, client administration, upgrades, backups, recovery, security, troubleshooting, database administration, SAP integrations, high-availability replication, clustering, and system migrations. The role also supports Oracle, SQL, and DB2 databases, SAP tools, Linux/Unix environments, and HANA scale-up and scale-out configurations.

Develop and maintain interactive Tableau dashboards and reports, translate business requirements into visualization specifications, optimize SQL queries and data models, perform ETL, ensure data accuracy, and troubleshoot data issues. Collaborate with cross-functional teams and communicate insights to technical and non-technical stakeholders. This remote individual contributor role supports global operations during a 2:00 PM to 11:30 PM IST shift.

Analyze compliance, AML, and financial markets processes; identify and mitigate risks; develop policies and procedures; monitor regulatory compliance; research financial regulations; prepare management reports; collaborate across business units; support training and regulatory inquiries; and provide staff guidance.

Develop Azure data pipelines and Databricks Lakehouse solutions using Azure Data Factory, Azure SQL, SQL, and PySpark. Convert Informatica PowerCenter and Oracle PL/SQL code, curate and transform structured and unstructured data, implement data models and Delta Lake tables, and support SQL Server cloud migration. Use Azure services including ADLS and ADX, automate delivery through DevOps and CI/CD, estimate project effort, and lead complex development in an agile environment.

Develop backend and full-stack applications using Core Java, Java EE, ReactJS, JavaScript, TypeScript, SQL, and related technologies. Build scalable software in large-scale, multithreaded, distributed environments; work with RESTful services, relational databases, and Linux. Collaborate with distributed teams, manage stakeholders, learn new tools quickly, and contribute to frontend development using HTML5 and CSS4.

Build responsive React interfaces, develop GraphQL and REST integrations, design SQL or NoSQL schemas, deploy applications on AWS, contribute to Terraform infrastructure, create Playwright automated tests, troubleshoot full-stack issues, and participate in code reviews, DevOps, CI/CD, and architecture discussions.

The Senior Data Scientist will analyze large datasets, develop ML/AI models, collaborate with teams, and ensure data quality and compliance.

The Lead Data Scientist will analyze large datasets, develop ML/AI models, collaborate across teams, and ensure data quality and compliance.