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EY-GDS Consulting-Full Stack Developers For Data Engineering-Manager

EY-GDS Consulting-Full Stack Developers For Data Engineering-Manager

7 - 10 years

14 - 19 Lacs

thiruvananthapuram

Posted:6 days ago| Platform:

Apply

Skills Required

full stack api gateway data pipelines investment banking react sql lambda java iam jenkins architecture azure s3 snowflake python github llm data engineering javascript angular grafana azure ml gds terraform aws

Work Mode

Work from Office

Job Type

Full Time

Job Description

Development Lead (Full Stack experience)

Work across investment technology stacks, engage directly with global stakeholders across investment, operations, products and wider technology teams and help drive technology solutions that support portfolio management and trading
Drive full stack application development using modern technologies across cloud-native and hybrid architectures
Own the production environment operations and applications

Required

7- 10 years of software engineering experience with at least 3 years in a lead role

Proven ability to led teams and drive cross-functional delivery in a matrix environment

Strong command of full stack development: Javascript (React/Angular), Node.js or Java/.NET/ Python and SQL

Hands-on experience with AWS architecture and services (Glue, Lambda, API gateway, IAM, S3, CloudWatch etc.)

Prior experience working in the Asset Management, Investment Banking or Wealth Management.

Build and maintainCI/CD workflowsfor model and data pipeline deployment using GitHub Actions, Jenkins, and Terraform
Familiarity with Snowflake, Python and event driven architecture
Develop and monitor
Grafana dashboards
for real-time observability, latency tracking, and cost optimization
Integrate
LLM APIs
(e.g., OpenAI, Gemini) into data services and applications for prompt engineering and inference workflow
Familiarity with Snowflake, Python, Pyspark and event driven architecture s.
Experience with Vector Databases, Familiarity with Feast, Sagemaker, Azure ML pipelines.

Desirable

Knowledge of front office platform and workflows: OMS, PMS and risk engines

Experience with ETF platforms and fund lifecycle processes

Exposure to regulatory reporting, ESG data pipelines or performance attribution systems

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