We are looking for a highly skilled Data Engineer with strong expertise in real-time streaming technologies and enterprise data engineering to join a leading digital transformation initiative within the banking domain.

The ideal candidate should have hands-on experience in designing scalable data platforms, enterprise data warehousing, streaming pipelines, and up-to-date data architectures using technologies such as Apache Flink, Kafka, and Java.

This role will be responsible for building and managing enterprise-grade data ecosystems that support real-time analytics, regulatory reporting, business intelligence, and digital banking products.

Enterprise Data Engineering & Modeling

- Design, develop, and manage Enterprise Data Warehouse (EDW) models including:
- Conceptual
- Logical
- Physical
- Virtual data models

- Build scalable and optimized data models for enterprise analytics and reporting.
- Design and implement:

- Raw Data Vault
- Data Lake
- Data Warehouse
- Data Marts

- Define standards and best practices for data modeling methodologies and design patterns.

Real-Time Data Streaming

- Design and develop real-time streaming pipelines using:
- Apache Kafka
- Apache Flink
- Java

- Build low-latency, high-throughput streaming architectures for banking and financial systems.
- Handle real-time ingestion, transformation, enrichment, and processing of large-scale datasets.

Data Architecture & Governance

- Recommend and implement suitable data storage technologies including:
- RDBMS
- NoSQL
- Big Data platforms
- Document Databases

- Define metadata management, data lineage,



business glossary, ownership, and derivation logic.
- Drive data quality, profiling, governance, and master data management initiatives.
- Establish standards for:

- Naming conventions
- Data definitions
- Documentation
- Change management

Stakeholder & Delivery Management

- Collaborate with business, analytics, and engineering teams to deliver scalable data solutions.
- Liaise with operational and support teams to ensure data processing SLAs are maintained.
- Guide developers and data modelers on enterprise data architecture and best practices.
- Support adoption of modern data warehouse technologies and banking industry-standard data models.

Required Skills & Experience

Core Technical Skills

- Strong experience in:
- Apache Flink
- Apache Kafka
- Java
- Real-time streaming architectures

- Expertise in:

- Enterprise Data Warehousing (EDW)
- Data Modeling
- Data Lake architectures
- Data Vault modeling

- Strong SQL and database design skills.
- Experience with relational and non-relational databases.

Preferred Experience

- Banking or financial services domain experience is highly preferred.
- Experience working on digital banking, payments, analytics, or enterprise data transformation programs.
- Exposure to cloud-based data platforms and big data ecosystems is a plus.

Preferred Candidate Profile

- Strong problem-solving and analytical mindset.
- Ability to work in large enterprise environments.
- Experience handling high-volume, mission-critical data systems.
- Excellent communication and stakeholder management skills.

📌 Data Engineer - Enterprise (Bengaluru)
🏢 Nameless
📍 Bengaluru