Top SQL Jobs in Hyderabad

Lead the design and development of quantitative data engineering models, algorithms, data pipelines, and processing systems on AWS using Python. Build scalable pipelines that ingest, transform, validate, and aggregate large datasets. Develop statistical and machine learning algorithms, optimize performance, evaluate models, create visualizations, and document methodologies. Collaborate with data scientists, analysts, and business stakeholders to deliver reliable customer-facing quantitative solutions and actionable insights.

Develop and maintain full-stack software across development, testing, and deployment. Design REST API backends, write SQL, optimize production code, enforce engineering best practices, and build reusable core components. The role requires independent decision-making, accountability, critical thinking, and strong communication while contributing to products serving immunization data and public health clients.

Analyzes complex datasets, develops Tableau dashboards, performs statistical and predictive modeling using R and Python, and delivers actionable insights. Partners with cross-functional teams and business stakeholders to identify inefficiencies, support strategic decisions, and monitor solutions. Requires strong communication, problem-solving, and analytical skills.

Design, build, and operate Databricks-based data and AI platforms using Medallion Architecture, Spark, Delta Lake, and scalable ELT pipelines. Integrate enterprise systems, implement data quality and monitoring, enforce governance and security, manage cloud data lakes, and enable ML/AI workflows with MLflow. Maintain documentation, conduct code reviews, train stakeholders, and report progress against project milestones.

Design, develop, and deploy enterprise data pipelines and data products using AWS and Databricks. Build Medallion Architecture pipelines, write Python, PySpark, and SQL code, optimize data workflows, troubleshoot production issues, and implement CI/CD using Databricks Asset Bundles, GitHub Enterprise, and GitHub Actions. Work hands-on across the full data engineering lifecycle in an Agile/Scrum environment.

Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Azure Data Factory, Databricks, PySpark, Python, and SQL. Transform large datasets, optimize data ingestion and queries, monitor pipeline performance, resolve data quality issues, support data modeling, document engineering standards, and contribute to cloud data infrastructure improvements. The role also involves collaboration with architects and senior engineers and requires familiarity with Azure Synapse, Delta Lake, governance, and security.

Develop and maintain high-performance backend services in Rust using asynchronous programming, REST APIs, databases, Redis, messaging systems, Docker, Kubernetes, and AWS. Responsibilities include writing tested and maintainable code, participating in code reviews, troubleshooting production issues, optimizing performance, implementing monitoring and error handling, and collaborating with senior developers, QA, DevOps, and product teams.

Build and maintain infrastructure and integrations that move CMS, SCADA, and other customer data into cloud platforms. Monitor and resolve connectivity issues, support AWS infrastructure, respond to data support tickets, collaborate with service delivery teams, and improve connectivity processes for scalability and reliability. The role requires Linux command-line expertise, knowledge of data protocols, networking, and IT security, plus flexibility to support global operations outside normal business hours.

Principal Data Engineer responsible for developing and supporting Databricks pipelines, integrating heterogeneous healthcare data sources, modeling unified data products, and ensuring data quality and availability. The role partners with business stakeholders, product teams, data engineers, and clinical leaders to gather requirements, create datasets, support ad hoc analytics, enable machine learning and AI use cases, and assist with acquisition integrations. Extensive healthcare data, cloud, SQL, PySpark, and Python experience is required.

Own and prioritize product backlogs, define user stories and acceptance criteria, lead Agile ceremonies, approve releases, and translate business needs into technical solutions. Analyze workflows, integrations, data flows, and enterprise platforms while aligning products with banking regulations. Use SQL, Power BI, and Tableau for data validation and dashboards, and govern UAT, QA scenarios, and defect resolution. Serve as a strategic advisor to executives and clients across media, pharma, and financial technology initiatives.

Design, build, and deploy AI/ML and Generative AI solutions for enterprise use cases. Build and maintain end-to-end ML pipelines, deploy models to production, and implement monitoring, observability, and model-drift detection. Work with APIs, vector databases, embeddings, and RAG-based applications, and collaborate with cross-functional teams to optimize scalable AI deployments.

Design, build, and optimize orchestrated data pipelines using dbt, Airflow, Azure Databricks, PySpark, SQL and Python. Implement CI/CD and automation, ensure data quality, perform ad-hoc analysis and reporting, collaborate with cross-functional teams, and troubleshoot DAG failures to support data-driven decision-making.

Validate AI voice bot functionality by creating/executing test cases from business documents, running functional/regression/integration/API tests, verifying conversational flows and intent recognition, supporting automation efforts, managing defects, and assisting production validation and release activities.

Lead design, build, deploy, and monitor enterprise-scale AI/ML and Generative AI systems. Own end-to-end ML pipelines, scalable inference, vector search and RAG applications, MLOps, observability, governance, CI/CD, model lifecycle management, and production support. Mentor teams, collaborate with stakeholders, and optimize AI systems for scalability, latency, reliability, and cost.

Develop and deploy AI agents, integrations, automations, and workflow solutions for customers. Build knowledge graphs and connect SaaS and non-SaaS systems using APIs, webhooks, and real-time architectures. Optimize AI performance through prompt engineering and semantic search, analyze data with SQL, create dashboards, prototype solutions, conduct technical demonstrations, and collaborate across customer-facing and internal teams. The role involves approximately 30% customer engagement and up to 80% travel.

Supports the analysis, design, testing, troubleshooting, documentation, and lifecycle management of enterprise integration and automation solutions. Works with APIs, microservices, databases, B2B and supplier integrations, EDI, workflow automation, and data quality. Collaborates with stakeholders, architects, and developers to gather requirements, configure solutions, perform quality assurance, manage risks, resolve incidents, and maintain integration components and documentation.

Design, develop, test, and maintain Java/J2EE backend and frontend features. Build UI components with HTML, JavaScript, and CSS; optimize SQL and relational database interactions; participate in code reviews and unit testing; troubleshoot production issues; collaborate with QA, product, and engineering teams; and lead technical design discussions and documentation.

Leads an offensive security team within an MSSP, overseeing attack surface discovery, application security testing, red teaming, adversarial simulations, vulnerability assessments, and ransomware resilience testing. Develops cybersecurity services, guides research and automation, and presents technical findings to executives. Requires deep expertise in offensive security, cloud and container security, CI/CD testing, exploit development, attack surface management, and security tooling, plus substantial leadership experience.

Develop and lead GIS data migration strategies for utility-sector clients, including extraction, cleansing, transformation, loading, validation, and integration. Build ETL workflows using FME, ArcGIS, and Python; manage enterprise spatial databases; design Utility Network data models and validation rules; document processes; support training; and mentor distributed teams.

Leads QA strategy and quality engineering across web, mobile, API, and backend systems. Owns test planning, automation, risk assessment, defect triage, release sign-off, quality metrics, and end-to-end data validation. Partners with Product and Engineering teams to improve testing practices, secure sensitive healthcare data, and drive reliable releases. Mentors QA engineers, reviews test assets, and promotes shift-left quality across the software development lifecycle.

Design, build, and maintain scalable ETL/ELT data pipelines and Snowflake-based data warehouses on AWS. Implement ingestion, transformation, orchestration, data quality, performance tuning, and monitoring; collaborate with stakeholders and troubleshoot production data platform issues.

Lead a Java engineering team to design, build, and operate scalable, secure, low-latency FinTech microservices. Drive architecture, SDLC best practices, cloud deployments, observability, compliance (PCI/GDPR), high-volume data processing, and cross-functional collaboration while mentoring and recruiting engineers.

Develop scalable full-stack applications using Python, Vue.js or React, JavaScript, and TypeScript. Design RESTful APIs, databases, data pipelines, and Kafka streaming applications. Deploy and optimize cloud-native solutions on Google Cloud Platform using Terraform, Kubernetes, Jenkins, and Argo CD. Maintain CI/CD pipelines, observability, security, compliance, and HIPAA-aligned practices while collaborating with technical and business stakeholders.

Develop and optimize data pipelines and workflows on GCP using BigQuery, dbt, and Airflow. Responsibilities include data modeling, advanced SQL, BigQuery tuning and cost management, dbt governance, data quality testing, CI/CD, infrastructure as code, cloud security and IAM best practices, and cross-cloud pipeline development. The role also requires maintaining dimensional models, SCDs, macros, and Airflow workflows.

Develops and maintains Power BI reports, dashboards, SQL queries, and analytics solutions. Translates stakeholder requirements into technical specifications, analyzes trends, supports reporting strategy, and provides stakeholder training and issue resolution. Collaborates on projects, system integrations, application development, DataStage production deployments, ETL scripting, and performance optimization across SQL, Access, and Excel reporting environments.