Top SQL Jobs in Hyderabad

QA Engineer II owns quality for assigned user stories and small features, designing and executing manual and automated tests (Playwright/JS/TS). Responsibilities include UI/API/database/end-to-end testing, maintaining regression suites, integrating tests into CI/CD, defect triage, using AI-assisted testing tools responsibly, and mentoring junior QA engineers while participating in Agile ceremonies.

Manage a high-volume tech-touch customer portfolio driving scalable adoption through automated lifecycle journeys, telemetry-driven health scoring, and segmented digital engagement. Build enablement assets, run automated renewal workflows, monitor support trends to prevent escalations, and optimize CRM/CS platform hygiene and playbook automation to improve adoption, retention, and operational efficiency.

The Senior Data Engineer will build and optimize data pipelines in Azure Databricks, migrate existing pipelines from Azure Synapse, and design scalable data models to support a financial services client's data platform modernization.

The role involves administering Salesforce, developing automations with Flows and Apex, and maintaining data pipelines to support revenue operations at ElevenLabs.

Senior Node.js developer responsible for building large multi-tenant web and client-server applications. Requires 5+ years Node and SQL experience, cloud development (AWS/Azure), RESTful API design, strong OOD/design patterns and security/authentication knowledge. Works in Agile teams; Ruby experience and advanced degree are a plus. Must be authorized to work in the U.S.

Lead design and delivery of enterprise BI solutions using Power BI and Microsoft Fabric. Build data models, dashboards, real-time analytics, and AI-powered insights. Collaborate with stakeholders, Data Engineering, and US leadership to turn complex requirements into scalable, high-performance reports and analytics solutions.

Lead the development and execution of product roadmaps, analyze market trends, collaborate with cross-functional teams, and deliver impactful solutions in Healthcare-FinTech.

Owner of company-wide reporting and analytics for Growth, Marketing, Product, Finance and Operations. Build and maintain dashboards, automated reports and data pipelines (dbt), ensure data quality and governance, run growth and product analyses (CAC, ROAS, LTV, retention), support A/B testing and ad-hoc decision support, leverage AI for automation, and coordinate VAs on data tasks.

Lead architecture and technical direction for a scaling SaaS platform. Modernize and evolve distributed systems, databases, and cloud infrastructure; improve reliability, observability, and CI/CD; mentor engineering teams and set organization-wide engineering standards.

Design, build, and optimize Databricks-based big data pipelines and ETL workflows using Spark, SQL, and Python/Scala. Maintain data lakehouse architectures, enforce governance and security, automate CI/CD and IaC, monitor cluster performance, and collaborate with data teams to enable AI/ML workflows.

Design and own end-to-end data platform architecture, build ingestion and transformation pipelines, model multi-tenant datasets, optimize Postgres and ClickHouse performance/cost, implement orchestration and observability, define data quality and reconciliation standards, and mentor data/product engineers.

Lead design, build, and operation of AI-powered product features across backend, frontend, and AI systems. Make architecture decisions, drive production deployments, improve code quality and reliability, mentor engineers, and own features end-to-end.

Build and productionize AI features across frontend and backend: document review, entity extraction, quote comparison, embeddings and LLM integrations, prototype from customer feedback, and create scalable reusable systems for insurance workflows.

Build and operate ingestion and transformation pipelines to turn messy insurance data into clean datasets. Design bronze/silver/fact layers, model and tune Postgres and analytical stores, define KPIs and reconciliation checks, orchestrate observable data jobs, and ensure end-to-end data quality for analytics and AI products.

Build AI-powered product features across backend, data pipelines, and UI. Implement RAG, embeddings, vector search, prompt design, and tooling to convert messy insurance documents into reliable, source-cited capabilities and collaborate with product and customer teams.

Remote internship supporting recruiter data operations: clean and analyze data, maintain website hosting and data structures, build API calls and automation scripts, perform web scraping, and communicate findings to stakeholders.

Design, build, and scale cloud-native Python backend services and data-backed applications. Develop RESTful APIs, microservices, and asynchronous event-driven systems. Deploy and operate production workloads on Kubernetes and at least one public cloud (AWS or Azure). Work with cloud data warehouses (Snowflake or Databricks) and relational databases, ensuring scalable, reliable distributed systems.

Design, develop, and maintain SAP BODS ETL jobs for data extraction, transformation, and loading. Collaborate with analysts and DBAs, implement data quality checks, optimize job performance, document data mappings and lineage, and support data modeling for BI and reporting.

Build and prepare data pipelines: mapping, cleansing, transformation, integration, and wrangling using Python and SQL. Perform feature engineering for structured and unstructured data and support API and web app deployment for data products.

Develop and maintain web applications using .NET, SQL, and APIs; implement responsive frontends with React (or Angular/Bootstrap); ensure performance and quality; participate in Agile/Scrum ceremonies; collaborate with cross-functional teams; follow version control and deliver solutions on schedule. Immediate joiner preferred.

Design, build, and maintain scalable ETL/ELT data pipelines on GCP/BigQuery using Python and Spark. Integrate systems (APIs, Oracle EBS), implement workflow orchestration, ensure data quality and security, monitor performance, and document processes while collaborating with analysts and business teams.

Design, develop, test, and maintain high-performance, scalable Java/Java EE applications. Participate in full SDLC, produce efficient, testable code, assist releases, and support architectural reviews and continuous improvement.

Design, build, and maintain scalable ETL/ELT pipelines and microservices for marketing and product data, ingesting from ad platforms (especially Meta Ads) and event systems. Enable campaign performance tracking, lead funnel analysis, attribution, and revenue reporting. Ensure data quality, observability, governance, and documentation while collaborating with marketing, growth, and analytics to deliver actionable datasets and drive business outcomes.

Design, operate, and secure scalable batch and streaming data pipelines and platforms. Own ingestion, transformation, serving, data quality, and access controls. Partner with product, risk, compliance, and InfoSec to ensure production reliability, correctness, and audit readiness for financial data.

Design, build, and optimize scalable data pipelines and models using Spark, Kafka, Airflow, dbt, and SQL across GCP and AWS. Ingest and normalize marketing and analytics data, ensure data quality and governance, support analytics and reporting, and collaborate with cross-functional global teams.