Data Engineering Lead

Description

Design and implement clean modular efficient Python (3.x) codebases for backend services data pipelines and LLM integrations.

Integrate with external Document AI / LLM systems via RESTful APIs codifying prompts into productiongrade code and managing their lifecycle (versioning tuning concepts template integration).

Architect and evolve MongoDB schemas with expert handling of embedding vs referencing strategies schema migrations and performance tuning.

Perform CRUD operations indexing backup strategies and monitoring on MongoDB Atlas hosted on AWS; manage VPC peering IAM roles and serverless triggers if needed.

Build and maintain cloudnative scalable secure data systems primarily on Azure or AWS.

Ensure high standards of quality with unit testing CI / CD pipelines and coding best practices.

Lead handson development while collaborating closely with Data Scientists Product Managers and DevOps teams.

Champion a highquality productiongrade approach to LLM prompt engineering and backend data services.

Monitor technological trends in AI integration NoSQL technologies and cloudnative data architectures to keep Neurons tech stack futureproof.

The Requirements

Please enter the minimum criteria skills education licenses etc. required to do this job

Mandatory Skills

Python Development

oStrong proficiency in Python 3.x backend and scripting tasks

oExperience integrating with Document AI / LLM systems (e.g. OpenAI Azure OpenAI) via APIs

oGood understanding of RESTful API concepts and integration patterns

oAbility to codify prompts manage their lifecycle and integrate templates into production LLM pipelines

oFamiliarity with unit testing CI / CD pipelines (e.g. GitHub Actions Azure DevOps)

Data Analytics Exposure

oFamiliarity with endtoend data analytics workflows including data preparation transformation and insight delivery

oAbility to support or collaborate with analytics teams to ensure backend systems support analytical use cases

oExperience working with WTWs Radar platform is a strong plus

Document Database Expertise

oStrong experience working with document databases for highperformance applications MongoDB preferred

oProficiency in schema design including embedding vs referencing strategies

oHandson experience with CRUD operations indexing performance tuning and schema evolution

Cloud Platform Familiarity

oStrong familiarity with Azure or AWS services relevant to data and backend application hosting

oBonus : experience with AWS / Azure SDKs in Python

Qualifications

General

o812 years of total experience in data engineering backend development and / or cloudnative application development

oAbility to operate both strategically (solution architecture) and tactically (coding handson)

oExcellent communication and documentation skills to share complex ideas with technical and nontechnical stakeholders

NicetoHave Skills

Experience finetuning or customizing LLMs beyond just API integration.

Familiarity with data governance frameworks and data quality best practices.

Experience in insurance financial services or digital platform environments.

Exposure to serverless cloudnative architectures.

Understanding of secure software development practices in regulated environments.

Key Skills

Administrative Skills,Facilities Management,Biotechnology,Creative Production,Design And Estimation,Architecture

Employment Type : Full-Time

Experience : years

Vacancy : 1