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Known analytics brand, metro locations, mid-level generalist backend title, and broad skillset increase competition.
Backend and data engineering skills are moderately transferable across industries.
Explicit 6–10 years requirement plus mandatory Python, PySpark, cloud, and integration skills.
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Design, develop, and maintain scalable backend services, APIs, microservices, and distributed data pipelines primarily using Python and PySpark.
Build and support enterprise integrations across systems like Salesforce, SAP, SharePoint, databases, cloud services, and AI-driven platforms ensuring data quality, governance, and near real-time business process integration.
Develop and operate cloud-native data platforms on AWS/GCP, including CI/CD pipelines and monitoring, to enable scalable, secure, and reliable backend and data engineering environments.
6–10 years of software engineering and integration experience.
Strong Python development expertise and experience in backend application and API development.
Hands-on experience with ETL/ELT frameworks, PySpark, enterprise integrations (Salesforce, SAP, SharePoint), relational databases (PostgreSQL, MySQL), and cloud technologies (AWS Glue, S3, Lambda).
Bachelor's or Master's degree in Computer Science, IT, Data Engineering, or a related field; immediate to 30 days notice period required; locations include Bangalore, Hyderabad, Pune, Chennai, Coimbatore, Gurugram, Noida - Hybrid.
Senior engineer skilled at building scalable, secure backend systems and event/API-driven enterprise integrations across complex SaaS and on-prem systems.
Experienced with distributed data processing and cloud-native data engineering on AWS/GCP aiming to drive modernization and automation.
Collaborates cross-functionally with product, AI, analytics, and business teams to deliver measurable improvements in enterprise data platforms and business workflows.