Data Engineering – Hadoop
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Salary
≈ $21k – $46k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 8+ years exp
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 28, 2026.
Overview
Company
Impact
Profile match
TeamPlus Staffing Solution, also known as Team Plus India, is an IT staffing and recruitment firm based in Pune that provides staff augmentation, contract and temporary staffing, contract-to-hire, permanent and executive placement, offshore staffing and recruitment process outsourcing. It recruits for client companies across Indian technology hubs including Bengaluru, Pune, Chennai, Hyderabad, Noida, Gurgaon and Kochi, and also markets AI engineering talent to overseas clients. Its listings are mostly client vacancies for data engineers, AWS cloud support engineers, DevOps and QA engineers, .NET and SAP ABAP developers, PCB and Creo design engineers and BI engineers.
Experience: 8+ Years
Industry: Fintech / Financial Services
Notice Period: Immediate to 30 Days
Job Summary
We are looking for an experienced Data Engineering Manager with strong hands-on expertise in Big Data, Data Warehousing, Distributed Data Architecture, Python/Scala, SQL, Hadoop, and AWS.
The candidate will be responsible for designing, developing, and maintaining scalable data pipelines, data warehouses, data marts, and large-scale data processing systems.
Mandatory Technical Skills
- Python / Scala: Strong hands-on development experience with production-grade data engineering systems.
- SQL & Data Warehousing: Advanced SQL, data modelling, query optimization, and large-scale data warehouse design.
- Hadoop Ecosystem: Strong understanding of Hadoop architecture, HDFS, YARN, and MapReduce.
- AWS Cloud: Hands-on experience designing and developing data pipelines using AWS services.
- Big Data & Distributed Systems: Experience with high-volume data processing, distributed architecture, and performance optimization.
- ETL / Data Pipelines: Strong experience building scalable ETL/ELT pipelines, data marts, and data frameworks.
- API Development: Hands-on experience in API development, publishing, and integration.
- Data Processing: Experience handling structured, unstructured, and streaming datasets.
- Performance Tuning: Experience identifying and resolving production performance bottlenecks.
- Leadership & Communication: Ability to collaborate with global engineering teams, guide developers, and manage multiple projects.
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