Top SQL Jobs in Hyderabad

Founding Sales Engineer responsible for technical discovery, tailored demos, pilots, integrations, security reviews, RFPs, and technical deal support for an AI-powered customer intelligence platform. The role partners with Sales, Product, and Customer Success, builds reusable demo and pilot infrastructure, translates enterprise requirements into proven solutions, and supports handoff to onboarding. Requires 5+ years of customer-facing technical pre-sales experience, SaaS integration expertise, API and SQL skills, AI tool familiarity, strong communication, and an entrepreneurial mindset.

Provide ad-hoc data and reporting support to Sales and internal teams using SQL, Databricks/Count, and spreadsheets. Clarify requirements, investigate discrepancies, resolve basic data issues, support routine data operations, and create reusable queries/reports and documentation to enable self-service.

Own EULER’s data lifecycle, including instrumentation, validation, reconciliation, privacy, anonymization, canonical data modeling, analytics datasets, documentation, and production pipelines. The role requires strong SQL, software engineering practices, independent ownership, skepticism toward data quality, and clear communication. Preferred experience includes GDPR/LGPD, multi-tenant B2B SaaS, dbt, statistics, Cloudflare Workers, Postgres, Parquet, DuckDB, and Bubble.

Translates medication contracting and operational needs into system requirements, workflows, data mappings, and business rules. Partners with technical and business teams to support application enhancements, testing, user acceptance, defect resolution, release validation, documentation, training, and access controls. Uses SQL and Excel to investigate data issues and validate system outputs while collaborating with developers, data teams, product leaders, vendors, and health plan stakeholders.

Build and operate Oracle integrations across Fusion Cloud, E-Business Suite, and third-party systems using OIC Gen 3 and OCI. Responsibilities include integration development, mappings, adapters, security, error handling, testing, CI/CD, Gen 2-to-Gen 3 migrations, AI-agent-assisted development, production support, documentation, and knowledge transfer. The role requires strong Oracle integration, PL/SQL, cloud services, distributed delivery, and customer-facing communication skills.

Designs and maintains Salesforce Data Cloud solutions for audience segmentation, activation, real-time ingestion, and data governance. Responsibilities include developing SQL queries, configuring Data Extensions, Data Model Objects, Data Streams, Calculated Insights, and Computed Traits; architecting cloud integrations with Snowflake, AWS, Azure, or GCP; resolving data quality issues; and implementing consent and governance frameworks.

Build and deploy production-grade full-stack AI systems for clients and internal accelerators. Responsibilities include data modeling, ETL/ELT pipelines, SCD implementation, dbt transformations, Python/FastAPI services, Next.js applications, AI agent and RAG workflows, orchestration, CI/CD, and AWS/Azure cloud deployments. The role owns projects end to end, translates ambiguous requirements into technical solutions, communicates with business stakeholders, and contributes reusable data and AI assets.

Develop, maintain, and support AS400/iSeries applications using RPG (ILE and free-form), ACOM, and ShowCase Query. Participate in design, testing, Agile delivery, production support, change control, and SOX/IT security compliance. Collaborate with business and technical teams to estimate work, triage defects, and deploy changes to production.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

Develops Power BI dashboards, financial reports, Excel models, SQL queries, and data models. Analyzes financial and operational data, supports reporting automation, validates data integrity, and provides insights to cross-functional teams.

Own SAP S/4HANA Public Cloud design, configuration, integrations, extensibility, finance and procurement processes, data migration, reconciliation, user access, cloud administration, governance, testing, and support. Partner with Finance and business stakeholders to translate requirements into SAP solutions, maintain integrations and ETL pipelines, ensure data integrity, manage releases, and support audits and financial close activities.

Develop frontend features for the Arango Data Platform and ArangoDB UIs. Modernize legacy code by migrating to React and TypeScript, translate Figma designs into polished user experiences, integrate backend and AI/ML APIs, and collaborate across product areas including graph visualization, developer tooling, dashboards, and AI-powered interfaces. The role also involves increasing feature ownership, shaping requirements, and iterating on shipped products.

Maintains production system reliability through incident triage, monitoring, alert optimization, Kubernetes troubleshooting, root cause analysis, and 24/7 support. Develops automation using C#, Java, Python, PowerShell, or Bash; monitors CI/CD pipelines; supports self-healing solutions; documents incidents and postmortems; and ensures fintech compliance. Collaborates with engineering and global teams to improve availability, performance, security, and operational processes.

Analyze operational data and processes, identify bottlenecks, design scalable solutions, automate workflows and reporting with Python and SQL, build dashboards and monitoring, perform root-cause analysis, document logic and collaborate with product, engineering, and ops teams to improve automation and data quality.

Designs and maintains scalable data pipelines using AWS, Spark, Kafka, Airflow, and related technologies. Collaborates with product, data science, and business teams; develops reporting dashboards; documents data flows and runbooks; optimizes workflows; troubleshoots data processing issues; and supports Agile delivery and CI/CD practices.

Designs and maintains AWS data architectures, ETL/ELT pipelines, data warehouses, analytics datasets, dashboards, and visualization solutions. Uses SQL, Python, Spark, Glue, Lambda, S3, Athena, Redshift, and QuickSight to prepare, transform, validate, and govern data. Collaborates with product, engineering, and operations teams, optimizing performance, cost, scalability, and data quality while integrating data systems with AI and natural-language query tools.

Develop and optimize Supabase’s Data API based on PostgREST. Responsibilities include improving the PostgreSQL driver and performance, developing features, fixing bugs, resolving incidents and escalated support issues, improving observability, and debugging integrations across the Supabase platform. The role requires strong Haskell development, PostgreSQL and SQL expertise, Linux debugging, open-source contribution, and technical user support.

Own, stabilize, and scale production systems while partnering with transformation teams. Build backend services, APIs, data models, asynchronous workflows, and queue-based processing using Python or TypeScript/Node.js. Manage cloud environments, deployments, infrastructure as code, and SQL data pipelines. Establish engineering standards for testing, CI/CD, code reviews, and production readiness, including AI-generated software. Mentor engineers and modernize fragile internal tools without disrupting operations.

Develop and maintain scalable full-stack web applications using Python and modern frontend frameworks. Design RESTful APIs, manage SQL and NoSQL databases, collaborate on feature delivery, and ensure application performance, security, and scalability. Debug production issues, follow clean coding practices, and contribute to system design, microservices architecture, CI/CD, and DevOps practices.

Owns data architecture and scalable engineering systems for an AI-native finance platform. Responsibilities include canonical data modeling, configurable connectors, SQL/dbt transformation, warehouse optimization, orchestration, CDC, lineage, data quality, schema evolution, and audit-ready traceability. The role also supports curated data for ML and LLM systems, customer-hosted multi-cloud deployments, mentoring distributed engineers, and collaboration with AI, backend, product, and US-based leadership.

Build production AI systems for finance teams, including per-customer anomaly detection models, grounded natural-language generation, agentic workflows, and managed LLM integrations. Develop Python services with SQL and warehouse access in containerized customer deployments. Establish rigorous evaluation, anti-leakage, hallucination, grounding, and faithfulness controls, incorporate human confirmation checkpoints, and convert user feedback into durable model and system improvements.

Own core backend services for a finance AI platform, building reliable, configuration-driven computation systems over financial and operational data. Ensure results are traceable, reproducible, auditable, and correctly reconciled. Provide technical leadership through architecture, design reviews, engineering standards, and mentorship while partnering with data, AI, and product teams. The role involves production Python, advanced SQL and data modeling, multi-tenant or customer-hosted deployments, and high standards for correctness and system reliability.

Leads full-stack software engineering efforts, including application design, coding, API development, performance optimization, testing, debugging, code reviews, and architectural decisions. Owns CI/CD pipelines and infrastructure-as-code strategies, evaluates technologies, improves code quality and scalability, and collaborates with product, design, services, and DevOps teams. Develops secure applications handling protected health information in accordance with HIPAA standards.

Manage and optimize paid advertising campaigns across Meta and Google to drive profitable ticket sales. Responsibilities include budget allocation, A/B testing, audience and keyword management, conversion tracking, ROAS and CPA optimization, reporting, dashboard maintenance, and post-campaign analysis. The role also requires Arabic and English ad copy development, AI-assisted workflow improvements, and collaboration with creative, CRM, SEO, product, and commercial teams.

Designs and builds end-to-end data platforms on Google Cloud for regulated-sector clients. Responsibilities include developing reliable pipelines, modeling scalable data systems, optimizing performance and cost, ensuring data governance and regional compliance, and applying cloud networking and security practices. The role requires strong SQL and Python skills, client-facing communication, and ownership of project outcomes.