Data Engineer - Enterprise at GSSTech Group

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

13 Aug, 26

Salary

0.0

Posted On

15 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Apache Flink, Apache Kafka, Java, Enterprise Data Warehousing, Data Modeling, Data Lake, Data Vault, SQL, RDBMS, NoSQL, Big Data Platforms, Real-time Streaming, Data Governance, Metadata Management, Data Lineage, Master Data Management

Industry

IT Services and IT Consulting

Description

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 modern 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 & ExperienceCore 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.

Responsibilities

Design and manage enterprise-grade data ecosystems, including data warehouses and real-time streaming pipelines for the banking domain. Establish data governance standards and collaborate with stakeholders to deliver scalable analytics and reporting solutions.