Top SQL Jobs in Hyderabad

The Senior Software Engineer will design, develop, and support innovative solutions, collaborating with teams, analyzing requirements, and ensuring application performance in an agile environment.

Design, implement, and improve monitoring, alerting, and self-healing for WMS platforms. Ensure production stability and performance, perform root-cause fixes, integrate WMS with external systems via APIs/webservices, and enforce standards through solution reviews. Drive automated testing, deployment, code reuse, documentation, and regional/global WMS standardization while collaborating with IT and business teams to deliver scalable, secure warehouse solutions.

Senior Azure Data Engineer responsible for designing and implementing end-to-end data pipelines using Azure Databricks, Azure Data Factory, and PySpark. Work with Delta Lake, Spark SQL, and data warehousing concepts to build scalable ETL/ELT solutions; collaborate on analytics and Power BI integration. Availability for 2pm-11pm/12am IST shift required.

Design, develop, enhance, and maintain core product features across front- and back-end using PHP and modern JavaScript frameworks. Build APIs and reusable libraries, fix critical issues, review pull requests, and work in an agile, collaborative team to expand product functionality.

Design, develop, and maintain enterprise integrations and internal tools using AI-assisted development. Lead architecture decisions, mentor peers, perform troubleshooting, collaborate across teams, and document integration solutions while championing AI-driven best practices and quality.

Design, develop, and maintain scalable full-stack web applications using Java/Spring Boot and Angular or React. Implement RESTful APIs, work with relational databases, write testable code, participate in code reviews, troubleshoot production issues, and follow Agile/Scrum practices.

Manage, monitor, and optimize AWS Aurora (MySQL/PostgreSQL) databases. Perform installs, configuration, patching, upgrades, performance tuning, backups/restores, disaster recovery, migrations using AWS DMS, and infrastructure automation with Terraform. Ensure availability, security, and troubleshoot production issues.

Design and build scalable batch and real-time data pipelines using Spark, Kafka, Java and SQL. Develop ETL/ELT frameworks, streaming solutions, data models and cloud data warehouses. Automate workflows with Airflow/DBT, monitor reliability, collaborate with Data Science and Engineering, and follow governance, security, and cost-optimization best practices.

Develop and maintain scalable Python/Django back-end services and APIs, integrate front-end and back-end systems, work with relational databases, Unix, and shell scripting, and participate in web architecture design. Must have strong web development experience, version control knowledge, and be willing to work Hyderabad WFO shifts (3PM–12AM).

Design, build, and maintain scalable ETL/ELT data pipelines and data models. Orchestrate workflows with Apache Airflow, implement transformations with dbt, use BigQuery and GCS, ensure data quality and performance, and collaborate with analytics teams to support BI and analytics initiatives.

Design, build, test and maintain large-scale data architectures and pipelines (batch and real-time) on AWS. Implement ETL/streaming solutions using Python, PySpark, Kafka, Kinesis/Firehose, DBT, and data warehouses. Build data lake solutions, enable analytics/ML tooling, integrate graph DBs, and support stakeholders with data tooling, governance, monitoring, and documentation.

Build and maintain large-scale data architectures and pipelines using AWS and big-data technologies. Develop ETL/streaming solutions, design data lakes, support analytics and ML use cases, implement data governance, optimize queries, and collaborate with product and data stakeholders to deliver scalable, reliable data platforms.

Design, develop, and maintain scalable .NET Core/C# API solutions using Azure services. Implement serverless functions, event-driven workflows, CI/CD pipelines (GitHub Actions), containerization, and cloud data solutions while ensuring security, monitoring, and performance optimization.

The Data Engineer is responsible for optimizing data architecture and pipelines, collaborating with teams to deliver data solutions, and building analytics tools for business insights.

Owns quality for assigned software features from requirements review through release validation. Designs and executes manual, exploratory, API, database, integration, regression, and end-to-end tests; develops and maintains Playwright automation in JavaScript or TypeScript; integrates tests with CI/CD; investigates failures; reports defects; validates fixes; and advises on release readiness. Collaborates within Agile teams, uses AI-assisted testing tools responsibly, and mentors Associate QA Engineers.

Lead QA Engineer defines quality strategy, establishes testing standards across manual, automation (Playwright), API, performance and CI/CD quality gates, and leads release governance. Responsibilities include architecture and design reviews, performance testing guidance, root-cause analysis, mentoring QA engineers, and implementing AI-assisted testing practices to ensure release readiness and cross-team quality outcomes.

As a Senior Software Developer at STChealth, you will develop, test, and deploy applications, enhancing healthcare data management and analytics.

The Quality Assurance Analyst will validate software functionality, performance, and usability, conducting various tests and collaborating with cross-functional teams to ensure high-quality healthcare applications.

Participate in structured SAP training covering S/4HANA, business processes, configuration concepts, testing, documentation, and troubleshooting. Assist senior consultants with requirements gathering, issue tracking, process analysis, and project scenarios. Develop functional or technical expertise across SAP areas such as FICO, MM, SD, ABAP, Basis, BTP, and SuccessFactors, with mentorship and preparation for entry-level SAP consulting roles.

Designs and implements computer vision and machine learning algorithms for aquaculture applications. Responsibilities include developing prototypes, conducting experiments, building data-processing and training pipelines, maintaining model testing and statistical verification, extending AI codebases, documenting research, leading long-term research, recruiting talent, and tracking AI developments. The role may also involve production deployment, inference optimization, MLOps, cloud platforms, and occasional visits to aquaculture sites.

Provides customer-facing technical support by owning tickets from intake through resolution, meeting SLAs, troubleshooting data quality and integration issues, documenting solutions, and coordinating escalations. The role also contributes to knowledge management, pipeline monitoring, dashboards, AI agents, and workflow automation. Success requires accuracy, customer empathy, strong communication, systematic problem-solving, and the ability to manage multiple priorities in a remote, fast-paced SaaS environment.

Designs and executes comprehensive testing for complex Salesforce implementations in banking and financial services. Responsibilities include functional, regression, integration, system, API, and end-to-end testing; validating Salesforce configurations and external integrations; managing defects in Jira; supporting UAT and production validation; maintaining regression suites; analyzing quality risks and release readiness; and improving QA processes, automation, and testing methodologies.

Support and enhance Azure-based production data platforms, troubleshoot incidents, manage SLAs within a 24x7 support model, deploy optimizations and automation, and provide direct customer support while contributing to ongoing learning and certifications.

Join our Growth team as a Junior Product Manager to support product roadmap execution, collaborate across teams, conduct market research, analyze performance metrics, and assist in growth experiments with a focus on user-centric product development.

Design, build, and maintain production data pipelines and integrations across applications, databases, and cloud services. Support data architecture, ingestion, embedding workflows for AI, data quality, monitoring, and platform reliability. Collaborate with Full Stack and AI teams to deploy scalable cloud-based data infrastructure and establish data engineering standards and best practices.