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Staff Data Engineer (8-10 years' exp - Java/Python, Scala, Spark, Hadoop)
Visa
Bengaluru, IND
Full-time
Senior · 8+ years experience
Discovered 2 weeks ago
airflowawsazureazure-data-factorydatabricksdelta-lake
Free
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Role Overview
Staff Data Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems. In this role, engineers spend a significant portion of their time coding, working hands-on with code, data, and modern tools—including AI-assisted development, cloud services, and automation frameworks—to deliver secure, scalable, and high-quality technology solutions that drive business outcomes in the fintech sector. They collaborate with cross-functional teams such as product managers, designers, data scientists, QA, operations, and compliance to translate business requirements into robust technical solutions, all while adhering to best practices, security standards, and regulatory requirements. This is a hands-on role requiring both deep data engineering expertise and the ability to work across legacy modernization and new platform innovation. You’ll collaborate closely with the Agentic Engineer, ML teams, and business stakeholders to enable AI-driven insights and intelligent data orchestration.
Key Skills for This Role
airflowawsazureazure-data-factorydatabricksdelta-lake
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Qualifications
- Basic Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
- 8+ years of hands-on data engineering experience, including enterprise-scale data warehousing and pipeline design.
- Proven success supporting and modernizing SQL Server–based data warehouses in high-SLA environments.
- Production-level experience architecting Hadoop, Spark, and Databricks data pipelines.
- Expertise in ETL/ELT frameworks, data modeling, and schema design for analytical and operational use cases.
- Strong programming proficiency in Python, Java, or Scala.
- Hands-on experience with AWS or Azure (Glue, Synapse, Redshift, Delta Lake, S3).
- Familiarity with Kafka, Airflow, Kubernetes, and containerized data services.
- Understanding of RAG pipelines, vector databases, and AI data flows.
- Experience designing data pipelines and APIs compatible with Model Context Protocol (MCP)-based agent frameworks, enabling seamless integration between AI agents, data services, and enterprise APIs
- Strong SQL optimization, debugging, and production troubleshooting experience.
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