Top SQL Jobs in Hyderabad

Leads Center of Excellence initiatives for Snowflake and SnapLogic data engineering. Designs complex integration pipelines, develops Snowflake data models and dbt transformations, manages CI/CD workflows, automates processing with Python or Shell, and uses advanced SQL for analysis and troubleshooting. Provides technical leadership on best practices, security, scalability, and deployment while collaborating with cross-functional teams to deliver reliable data solutions.

The Senior Data Analyst designs scalable data models using Medallion Architecture, builds Power BI or Tableau dashboards, analyzes complex datasets, optimizes SQL queries, develops Python automation scripts, and works with Snowflake or similar cloud data warehouses. The role translates business requirements into technical specifications and delivers insights that improve reporting, operational efficiency, and strategic decision-making.

Designs and executes ETL testing strategies, performs data reconciliation and integrity assessments, optimizes SQL queries, validates data across PostgreSQL, MSSQL, and Snowflake, and develops automated data quality testing suites to ensure reliable data pipelines and reporting.

Lead the design, development, and implementation of scalable low-code applications on the Mendix platform for financial services. Translate business requirements into technical solutions, integrate applications with proprietary and third-party systems using APIs and web services, ensure quality and performance, and provide technical leadership. The role also involves staying current with Mendix updates and applying best practices across application development and deployment.

Supports development and operation of AI and machine learning platforms, including backend APIs, model integrations, Docker and Kubernetes deployments, Azure cloud services, CI/CD automation, monitoring, security, testing, and troubleshooting. Collaborates with engineering, machine learning, product, support, and business teams while completing required technology training and an AI-enabled deployment capstone.

Develop, test, deploy, and support production-ready machine learning solutions. Responsibilities include data preparation, exploratory analysis, baseline modeling, feature engineering, model evaluation, Python development, APIs, pipelines, containerization, MLOps, testing, monitoring, documentation, and responsible AI risk identification. The role supports classification, regression, clustering, forecasting, NLP, and generative AI use cases in a collaborative Agile environment.

Provides first-level operational and technical support for software, APIs, AI applications, and machine learning products. Responsibilities include ticket and incident management, troubleshooting logs and configurations, monitoring application and infrastructure health, documenting resolutions, creating runbooks, supporting testing and maintenance, coordinating escalations, tracking service metrics, and identifying automation opportunities.

Business Analyst translating business needs into clear requirements for data, analytics, and AI/ML products. Responsibilities include discovery workshops, process modeling, backlog refinement, business rules, build specifications, requirements traceability, UAT planning, AI output validation, defect triage, reporting, change control, and documentation. The role requires SQL and data literacy, Agile delivery experience, workshop facilitation, and the ability to define acceptance criteria for AI features. Experience with GenAI, LLMs, RAG, data governance, dashboards, or life sciences is advantageous.

Build and manage data pipelines, enterprise connectors, raw-to-mart data layers, metadata and semantic indexes, vector databases, data quality controls, lineage, governance, and audit data stores. Support RAG and LLM applications with grounded, traceable data. Required skills include Python, SQL, modern data platforms, orchestration, API integration, testing, Git, and CI/CD. Bonus experience includes unstructured content processing, knowledge graphs, regulated life sciences data, and cloud or platform certifications.

Design, build, and maintain scalable data infrastructure for digital and physical operations. Responsibilities include architecting data lakes and lakehouses, developing ETL and ELT pipelines, using Airflow and Spark, creating data models in Snowflake or Databricks, coding in Python, SQL, and Scala, and monitoring data platforms for reliability, security, and performance.

Develop predictive credit risk, underwriting, pricing, segmentation, and portfolio performance models. Analyze financial, behavioral, and merchant data; conduct experiments; refine credit policies; integrate models into production; and monitor performance for governance and regulatory compliance. Communicate analytical findings to technical and business stakeholders across Credit Risk, Product, Engineering, Underwriting, and Compliance.

Lead hands-on enterprise Power Platform engineering engagements, designing Dataverse architectures and building solutions with Power Apps, Power Automate, Azure, and custom code. Responsibilities include software development, integrations, ALM, CI/CD, troubleshooting, technical discovery, architecture decisions, client communication, technical leadership, mentoring, and establishing engineering standards. The role combines consulting, solution architecture, and player-coach leadership across complex client projects.

Supports business analysis for AI, software, ERP, and enterprise technology projects. Responsibilities include gathering and documenting requirements, mapping processes, validating AI applications, supporting UAT, preparing business cases and client materials, and participating in Agile delivery. The role collaborates with consultants, engineers, product managers, and stakeholders across India and Australia while contributing to digital transformation and technology consulting engagements.

Designs, builds, and optimizes scalable Databricks ELT pipelines using PySpark, SQL, dbt, and Delta Lake. Develops Bronze, Silver, and Gold data layers; implements ingestion, data quality, schema evolution, CDC, and incremental processing. Integrates pipelines with applications and APIs, tunes Spark workloads, supports ML datasets, and collaborates with architects, cloud engineers, modelers, and governance teams on secure, documented, enterprise-grade data platforms.

Supports Oracle EDI and B2B integrations across supply chain, order management, and finance processes. Responsibilities include gathering requirements, documenting specifications, onboarding trading partners, configuring and troubleshooting EDI mappings, managing connectivity, supporting production operations, investigating failures with SQL, conducting root cause analysis, coordinating testing and deployments, and improving integration reliability. The role requires collaboration with business stakeholders, Oracle technical teams, vendors, and external trading partners.

Designs, builds, and maintains scalable ETL pipelines connecting Salesforce with Snowflake and other data systems. The role manages Salesforce APIs and bulk data loading, writes and optimizes SQL and Python for data transformation, conducts Git-based code reviews, and monitors pipeline performance, availability, and data integrity.

Supports digital factory initiatives connecting ERP, MES, production planning, shop-floor execution, machine connectivity, and management dashboards. Translates manufacturing requirements into functional specifications, coordinates data validation and system implementations, develops operational analytics, supports traceability and material tracking, prioritizes digital improvements, and drives user training and adoption across manufacturing, engineering, quality, maintenance, and IT teams.

Leads UI/UX and full-stack engineering teams, owning end-to-end web delivery across front-end interfaces, REST APIs, and back-end services. Responsibilities include architecture, design system governance, technical risk management, hiring, talent development, performance management, and cross-functional collaboration. The manager also drives AI-assisted engineering practices using Claude and contributes to technical roadmaps, delivery reporting, and product quality.

Build and maintain Python FastAPI services, relational data models, SQL queries, and production database migrations. Develop Next.js and React interfaces with complex state, server components, route handlers, and caching. Own end-to-end architecture, observability, testing, system design, and code reviews. Apply principles including idempotency, retries, timeouts, consistency, authorization, tenant isolation, and event-driven systems.

Designs and maintains data warehouses, metadata frameworks, dimensional models, and ETL pipelines using SnapLogic or Informatica, Python, dbt, Snowflake, and SQL. Optimizes data systems, supports reporting and dashboards, and implements data governance practices. Collaborates with cross-functional teams to ensure data quality, integrity, security, and compliance while exploring Generative AI applications in data engineering.

Designs and maintains scalable Snowflake ETL/ELT pipelines, SnapLogic integrations, and dbt transformation models. Responsibilities include dimensional and medallion architecture, performance and cost optimization, data quality, governance, CI/CD, documentation, and responsible use of AI-assisted development tools. Partners with analytics teams, mentors junior engineers, and helps establish reusable AI workflows and engineering standards.

Performs functional, regression, retesting, end-to-end, and web automation testing; designs and executes test cases; validates backend data with SQL; documents and tracks defects; and collaborates with cross-functional teams to resolve issues. API testing and automation using REST Assured or Postman are preferred.

Build blockchain data models and datasets by reverse-engineering DeFi protocols, indexing blockchains, and transforming transaction logs, smart contract events, and state changes into structured data. Develop SQL/dbt models, real-time pipelines, lakehouse schemas, and quality metrics for analytics and machine learning. Detect wash trading, bot activity, and Sybil attacks while integrating heterogeneous data through APIs and JSON-RPC.

Own Supabase’s cloud and SaaS vendor relationships, including negotiations, renewals, procurement governance, spend visibility, reporting, and optimization. Build the procurement and FinOps function, develop cost dashboards and governance standards, drive savings through right-sizing and consolidation, and coordinate cloud efficiency initiatives. Manage a distributed team, roadmap, intake, and stakeholder alignment while partnering with Finance, Engineering, Legal, and vendors.

Designs, implements, tests, monitors, and supports REST API integrations between systems. Responsibilities include authentication and authorization configuration, data mapping and validation, troubleshooting API failures, production support, deployment assistance, performance monitoring, stakeholder coordination, and technical documentation.