We are hiring a skilled Data Engineer with a strong background in the Fintech domain to design, build, and scale robust data infrastructure. You will own end-to-end data pipeline development, enable AI/ML-driven investment research workflows, and help grow our platform from early-stage to production-grade systems in a fast-paced, collaborative environment.
Key responsibilities:-
- Scalable pipeline design — Build and maintain ETL/ELT pipelines for structured and unstructured financial datasets using cloud-native technologies.
- Real-time & batch processing — Develop and operate real-time and batch data processing systems for investment research and analytics workflows.
- Data integration — Integrate market, financial, and alternative data sources into a centralised data platform using APIs and streaming ingestion.
- Architecture optimisation — Optimise data warehousing and lakehouse architectures for performance, reliability, and scalability.
- AI/ML support — Collaborate with AI and ML teams to enable agentic workflows and intelligent automation at scale.
- Data governance & quality — Enforce data quality, governance, security, and compliance standards across all data assets.
- Platform scaling — Drive platform maturity from MVP to stable production systems; participate in architecture and system design reviews.
Required skills & experience:-
- 5+ years in Data Engineering (mandatory)
- Fintech / financial data domain experience
- Strong Python & SQL proficiency
- ETL/ELT pipeline development expertise
- Cloud platforms: Azure / AWS / GCP
- Databricks, Apache Spark, Apache Kafka
- Data warehousing & lakehouse architectures
- Streaming data & large-scale dataset handling
- CI/CD & DevOps practices for data platforms
- Data governance & security best practices
Pay: ₹1,000,000.00 - ₹1,500,000.00 per year
Application Question(s):
- Do you have experience handling real-time or batch financial/FinTech data pipelines and working with large-scale datasets or streaming data?
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Have you worked on cloud platforms like AWS, Azure, or GCP along with technologies such as Spark, Kafka, or Databricks?
- Do you have 5+ years of hands-on experience in Data Engineering, including building ETL/ELT pipelines using Python and SQL?
Education:
Experience:
- Fintech domain to design, build, and scale robust data: 5 years (Required)
Work Location: Hybrid remote in Bengaluru, Karnataka (Bengaluru)
