Data Engineer - Data and Generative AI @ Advisor360°

Data Engineer

We hire people with all kinds of awesome experiences, backgrounds, and perspectives. We like it that way. So even if you don t meet every single requirement, please consider applying if you like what you see.

Key Responsibilities

• Acts as a technical leader by making significant technical contributions to the planning and implementation of mid- to large-scale projects from conception to completion.

• Demonstrates versatility of knowledge and applies strong technical skill sets to architect and implement cloud-based data solutions.

• Validates requirements, performs business and technical analysis, designs cloud-native applications, writes optimized PySpark-based data pipelines, and contributes to end-to-end application development.

• Ensures compliance with coding standards and best practices for AI-assisted code generation, suggesting opportunities for improvement.

• Utilizes GenAI tools like Cursor, Claude, and other LLMs to decompose complex requirements and auto-generate UI, API, and database scripts for rapid development.

• Acquires and utilizes strong technical and application knowledge to introduce and forecast the impact of new software design patterns, AI-driven development workflows, and emerging cloud technologies.

• Shares information and expertise to improve team productivity and empower engineers with AI-driven automation.

• Acts as a subject matter expert (SME) within the organization, helping resolve complex technical issues related to cloud data engineering, distributed computing, and microservices architecture.

• Mentors team members and fosters collaborative learning environments, particularly in areas related to GenAI, Azure, PySpark, Databricks, and CI/CD automation.

• Leads multiple projects within the team, ensuring seamless integration of AI-driven development into software delivery pipelines.

Preferred Strengths

• Proficiency in GenAI-powered development, leveraging AI tools for code completion, optimization, and automated unit testing.

• Strong experience with SQL, relational databases, and GIT, including building and release definitions within a CI/CD environment.

• Expertise in Microsoft Azure cloud services, including Azure Data Factory, Azure Functions, and Azure Databricks.

• Familiarity with serverless architectures, containerization (Docker/Kubernetes), and big data frameworks like Apache Spark.

Requirements, Skills, and Knowledge

• 7+ years of software engineering experience building enterprise applications using Python, .NET.

• Proven ability to analyze, decompose, and automate requirement-based development using GenAI.

• Strong experience in building and deploying cloud-based data processing applications using PySpark and Azure Databricks.

• Hands-on expertise in automating and optimizing cloud infrastructure using Terraform, Bicep, or ARM templates.

• Experience implementing business-critical database applications, REST microservices, and real-time event-driven architectures using Kafka, Orkes, and Databricks.

• Deep knowledge of SDLC methodologies (Agile, DevOps) and experience leading technical implementations from architecture to production deployment.

• Proficiency in coding standards, code reviews, source control management, build processes, testing, and operations.

• Experience integrating AI-based automation for improving code quality, predictive analytics, and data-driven decision-making.

• While Wealth Management domain experience is a plus, it is not mandatory. Candidates should be willing to learn/master the domain through on-the-job experience.