Top Python Developer Jobs in Delhi

Develop datasets, evaluation methods, validation tools, and quality standards for robotics and embodied AI systems. Translate research needs into dataset specifications, design collection protocols, audit multimodal robotics data, and run experiments analyzing how data quality and structure affect model performance. Collaborate with research, engineering, data providers, and customers to improve robotics data offerings.

Design, build, and optimize scalable data pipelines and event-driven architectures on GCP. Develop Python applications, integrate external APIs, manage BigQuery and cloud storage solutions, and automate deployments with Cloud Build. Ensure pipeline performance, scalability, cost efficiency, data quality, governance, lineage, and security while collaborating with cross-functional teams and documenting technical solutions.

Build and maintain web and mobile systems supporting field-worker onboarding, device assignment, attendance, data collection, uploads, payments, dashboards, and operational workflows. Integrate storage and data-quality systems, improve reliability under poor connectivity, automate manual processes, monitor deployments, and troubleshoot production issues. The role partners closely with founders and operations teams, owning features end to end across frontend, backend, infrastructure, testing, deployment, and support.

Design, build, and optimize scalable ETL/ELT pipelines and event-driven data architectures on GCP. Develop Python applications, integrate external APIs, deploy cloud services, automate CI/CD with Cloud Build, and manage data quality, governance, lineage, security, performance, and cost efficiency. Collaborate with cross-functional teams to deliver scalable data solutions and maintain technical documentation.

Lead and own major components of DuckDuckGo's privacy technology using Go, Node.js, Python, and Perl. Design and implement privacy features, improve search and AI features without compromising privacy, build tracker-detection features, participate in privacy reviews and audits, and mentor engineers over time.

Own product metrics definitions and trees, investigate anomalies and conversion bottlenecks, validate hypotheses, conduct data mining, and prioritize growth opportunities. Design, monitor, and analyze A/B tests, including sample sizing, randomization, guardrail metrics, data tracking, quality checks, and actionable recommendations. Collaborate with Product and functional leads in a fully remote environment.

Leads the design, testing, documentation, and scaling of weather data pipelines that convert scientific forecasts into timely, location-specific farmer messages. Oversees data quality, automated processing, system replication across geographies and dissemination channels, technical requirements, and stakeholder coordination. Translates between forecast science, engineering, research, and program teams while guiding staff and contributing to funding proposals and institutional knowledge management.

Manage installation, maintenance, compatibility testing, and support for EDA tools across RF, ASIC, analog, and FPGA design environments. Maintain Synopsys and Siemens regression tools, validate open-source tools in Linux, run end-user sanity tests, and troubleshoot issues in GRID environments using Altair Accelerator, LSF, or SLURM. The role also documents support procedures, collaborates with infrastructure teams, and ensures efficient EDA resource utilization.

Designs and tests IP network implementations while providing expert technical support, operational guidance, real-time network analysis, and solution testing. Performs manual testing of Cisco routing and switching technologies, particularly Cisco IOS-XR platforms. Uses networking protocols and services including IP/MPLS, OSPF, IS-IS, BGP, Segment Routing, VPNs, and QoS. Automation, traffic-generation tools, troubleshooting, communication, and networking certification are important parts of the role.

Build and optimize ETL/ELT pipelines feeding BigQuery, audit and troubleshoot data quality, and create reliable Looker Studio dashboards. The role supports sales leaders by turning raw data into accurate, actionable insights, improving reporting performance, eliminating manual processes, and ensuring data integrity across Curvion’s revenue operations ecosystem.

Own business data as a trusted source of truth by building metrics, dashboards, reporting systems, and analytical frameworks. Analyze complex datasets with advanced SQL, define KPIs, identify trends and opportunities, and solve ambiguous business problems. Partner with business, marketing, finance, and other teams to translate analysis into clear recommendations and data-driven decisions.

Consolidate and modernize PALU and CIMS data and deployment systems across Databricks, AWS, GitLab CI/CD, PostgreSQL, and dbt. Responsibilities include assessing Databricks, building data pipelines and models, configuring CI/CD, optimizing AWS costs, implementing containers and infrastructure as code, managing security and backups, monitoring systems, resolving maintenance issues, documenting configurations, and training MCD staff for independent system operation.

Design, build, and maintain scalable data pipelines and ETL/ELT solutions using Microsoft Azure Fabric, Databricks, and Azure data services. Translate business requirements into technical solutions, optimize data workflows for performance and cost, troubleshoot production issues, and collaborate with architects, analysts, developers, and global stakeholders. Use AI-assisted development and automation to improve engineering productivity while owning delivery quality, timelines, and outcomes.

Supports Tableau dashboard development, operational reporting, requirements gathering, basic data analysis, T-SQL querying, and Excel-based reporting. Maintains data quality, documentation, and process materials while helping translate findings into summaries and presentations. Collaborates with senior analysts and cross-functional partners to deliver accurate reporting outputs.

Senior backend-focused engineer responsible for designing and delivering features in Go and React, building scalable distributed architectures, mentoring teammates, coordinating with product and business stakeholders, instrumenting production systems, and leading small teams to ship high-quality APIs and services.

Develop marketing budget allocation models, Early LTV metrics, performance diagnostic frameworks, and analytical tools. Analyze products, channels, campaigns, cohorts, attribution, and marketing economics using SQL, experimentation, BI tools, and spreadsheets. Support AI-based analytics development and unified BI metrics while translating findings into business rules and recommendations.

A 12-week, part-time technical training program for individuals without prior technical experience. Learners develop foundational skills in Linux, networking, web applications, databases, Python, and IT security through Pluralsight coursework. Successful graduates may be considered for an Akamai apprenticeship or future entry-level roles. Participants must commit approximately 10 flexible hours weekly, communicate effectively, collaborate well, learn independently, and be proficient in English.

Lead design and governance of secure, scalable multi-cloud and hybrid architectures. Define reference patterns, drive cloud migrations, implement IaC and observability, ensure security/compliance and operational excellence, and guide delivery teams on resiliency, cost optimization, and CI/CD enablement.

Lead the Platform Services engineering team responsible for shared infrastructure, internal tooling, and core services. Own distributed systems architecture, cloud reliability, observability, cost optimization, roadmap delivery, and incident management while remaining hands-on with code and production systems. Hire, mentor, and develop engineers; establish technical standards; and collaborate with product engineering, SRE, security, and leadership. Drive AI-assisted engineering practices and platform automation.

Manage Oracle and Microsoft SQL Server databases across on-premises and OCI environments. Responsibilities include administration, patching, upgrades, security, performance tuning, backup and recovery, cloning, refreshes, database links, and disaster recovery using Data Guard and SQL Server availability technologies. Conduct DR testing, troubleshoot production incidents, maintain runbooks, collaborate with technical teams, and participate in on-call support.

Designs and executes manual and automated tests for data ingestion, transformation, APIs, reporting, and end-to-end data flows. Validates ETL accuracy, business rules, API contracts, and data integrity using SQL, Databricks, Azure Data Factory, Postman, and Swagger. Manages defects, retests fixes, maintains regression coverage, supports release readiness, and collaborates with Product, Engineering, and Data teams to improve QA processes and automation.

Designs and executes manual and automated tests for data ingestion, ETL transformations, APIs, business rules, and reporting. Validates data integrity, pipeline outcomes, API contracts, and end-to-end workflows using SQL and cloud data tools. Documents and triages defects, supports root-cause analysis and fix validation, maintains regression coverage and traceability, and contributes to release readiness and QA process improvements while collaborating with Product, Engineering, and Data teams.

Provide first- and second-line application support for global users across rotating day and night shifts. Investigate incidents and service requests using logs, monitoring tools, SQL, API calls, and debugging tools. Troubleshoot Windows, Linux, databases, networking, and application issues; document incidents; manage SLAs; and collaborate with development, QA, infrastructure, and subject-matter experts to resolve complex problems.

Analyze CRM product usage, funnels, cohorts, feature adoption, A/B tests, and business impact. Build product, business, and reliability dashboards; investigate data discrepancies across applications, databases, pipelines, metrics, and events; establish automated data-quality checks; define issue taxonomies; configure metric alerts; and integrate new data sources using SQL, Python, Redshift, and related tools. Collaborate with product, engineering, finance, and data teams to improve data reliability and product decisions.

Design, develop, and optimize scalable data platforms, pipelines, and processing workflows supporting analytics, business intelligence, and AI applications. Build solutions with Databricks and cloud technologies, integrate structured and unstructured data, implement quality and governance practices, optimize architectures, and support production deployment and monitoring. Collaborate with cross-functional teams to translate business requirements into reliable technical solutions and troubleshoot complex data challenges.