Project Role : Custom Software Engineer

Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Must have skills : Scala

Good to have skills : NA

Minimum 5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

We are seeking an experienced Data Architecture Team Lead to define and drive the architecture of scalable, maintainable data pipelines for real-time banking data products. In this role, you will lead architectural decisions across the end-to-end data platform, including mainframe CDC ingestion, Confluent Kafka, Apache Spark Structured Streaming on Amazon EMR, and MongoDB Atlas. You will play a critical role in onboarding new applications, establishing architecture standards, and ensuring consistency, scalability, and reliability across the applicaiton.

Roles & Responsibilities:

Define and enforce architectural standards for real-time Spark Structured Streaming pipelines across the DDS platform

Lead architectural design for new application onboarding (NewApp KT) including data flow design, collection modeling and CDC subscription definition

Evaluate and propose improvements to existing pipeline architectures for performance, scalability and maintainability

Define MongoDB collection schemas, indexing strategies and write patterns (upsert, bulk write, TTL indexes)

Design Kafka topic structures, partition strategies and CDC subscription configurations in collaboration with IBM CDC and Confluent teams

Collaborate with cross-functional teams including HOST/mainframe, GFT, CDC squad and platform engineering

Produce and maintain architecture documentation — high-level design diagrams, data flow documents and ADRs (Architecture Decision Records)

Review technical designs proposed by development team members and provide architectural guidance

Support production deployments across INT, PRE and PRO environments on Amazon EMR

Technical Skills:

Must have:

Scala and Apache Spark — deep understanding of Structured Streaming internals, execution model and performance tuning

Data architecture — experience designing end-to-end real-time data pipelines

MongoDB — collection design, indexing, aggregation pipelines, Atlas architecture

Kafka — topic design, partition strategy, consumer group management, Confluent Cloud

AWS — EMR, S3, CloudWatch

Good to have:

IBM CDC / Change Data Capture — subscription design, table filtering, multi-table refresh

Delta Lake on S3

Banking domain knowledge — account movements, transaction processing, balance calculation

Jenkins, SonarQube, Bitbucket

Java

Desirable:

Experience with mainframe DB2 data structures

Knowledge of IBAN calculation standards

Experience with MongoDB Atlas cross-cluster architectures

Experience: Minimum 6 years of experience in data engineering with at least 2 years in a technical architecture or lead role.