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# Senior Cloud Data Engineer w/ Azure and Python

- **Company:** Intersources Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Franchise
- **Skills:** JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Application Lifecycle Management, Microsoft Azure, Cloud Database, Code Generation, Continuous Integration, Information Engineering, Data Infrastructure, Data Transformation, Data Warehousing, Cursor (Graphical User Interface Elements), Database Queries, Github, Python (Programming Language), Anaplan, Software Engineering, TypeScript, Application Enhancement Tool, GitHub Copilot, Large Language Models, Snowflake, Google Cloud Functions, Data Analytics, Software Version Control, Workday, Servicenow, Databricks, Programming Languages
- **Published:** June 9, 2026
- **Apply:** https://www2.jobdiva.com/portal/?a=62jdnw10t7d77ytz0lbaey9qxonk3b05a9tqw96rb7z6hlfo7xj79l9g6mp6aj2o&compid=0/jobs/32418557#/jobs/32418557

## About the Role

Seeking to hire individuals who are highly motivated, intelligent and have demonstrated excellence in prior endeavors. In addition, qualified candidates will possess the following:

5+ years of data science, analytics engineering or data-heavy application development experience, with a track record of building and shipping production products;

Proficiency in one or more programming languages such as Python, Julia, R or JavaScript/TypeScript;

Experience with at least one public cloud platform (Azure, AWS or GCP); familiarity with Azure services a plus;

Experience with CI/CD practices and source control tools such as GitHub or Azure DevOps;

Strong SQL skills and experience working with data warehouses or analytical data platforms; experience with Snowflake or Databricks a plus;

Familiarity with data modeling concepts and experience transforming raw data into clean, well-structured datasets for analytical use;

Strong communication skills and ability to collaborate with non-technical stakeholders.

Additional Experience We Value

Familiarity with Azure services such as Azure AI, Function Apps or Azure OpenAI;

Experience with enterprise platforms such as ServiceNow, Anaplan or Workday;

Prior experience in investment banking, financial services or a related industry, with an understanding of deal workflows, financial reporting or client-advisory processes;

Hands-on experience integrating LLM APIs (such as OpenAI, Anthropic or Azure OpenAI) into production applications or data workflows;

Comfort using AI-assisted code generation tools (such as GitHub Copilot or Cursor) as part of an active development workflow

## Description

Requirement Notes (Candidate Job description below) : We are looking for a developer with strong analytics instincts to join us at the intersection of AI, application development and financial services: someone who thrives on ambiguity, enjoys solving hard problems with financial data and is energized by applying emerging analytics tooling and AI capabilities to real business problems. In this role, you will work primarily with client-facing business units, contributing across the full application lifecycle from prototyping and design through testing, deployment and ongoing support. This is a high-visibility role where the work is meaningful and the people you build for are deeply engaged in what you deliver.

Our team of senior professionals delivers a wide array of strategic advisory, shareholder advisory, restructuring and special situations and private fund advisory and placement services to corporations, financial sponsors, institutional investors and governments around the world. We offer a unique portfolio of advisory services designed to help our clients achieve their strategic objectives. We also provide, through , private fund advisory and fundraising services for alternative investment managers, including private equity funds, real estate funds and hedge funds.

From the beginning has firmly believed that having the best people is key to building an enduring franchise. Our perspective was, and remains, that a great team brings in both top tier clients and appeals to a wide-range of diverse, talented colleagues. Fostering an inclusive culture, which welcomes differing perspectives and beliefs, enables us to provide the best advice and insights to our clients.

Responsibilities

The Technology team is responsible for creating and continuously improving a robust and secure technology foundation that supports the firm's business activities.

The Data & Applications team within Technology manages business-facing applications and builds the analytics products, AI-powered tools and data infrastructure that connect data, technology and decision-making across the firm. Team members combine finance and business expertise with technical skills in application development, data engineering and data analytics to deliver technology solutions across corporate functions and client advisory.

We are looking for a developer with strong analytics instincts to join us at the intersection of AI, application development and financial services: someone who thrives on ambiguity, enjoys solving hard problems with financial data and is energized by applying emerging analytics tooling and AI capabilities to real business problems. In this role, you will work primarily with client-facing business units, contributing across the full application lifecycle from prototyping and design through testing, deployment and ongoing support. This is a high-visibility role where the work is meaningful and the people you build for are deeply engaged in what you deliver.

Additional Responsibilities Include

Design, develop and deploy applications and analytics solutions that support client-advisory workflows, with a focus on making financial data more accessible and actionable across the firm;

Develop subject matter expertise on key financial data elements and business workflows, and translate that understanding into technically sound solutions, making independent decisions on feasibility, tooling and architecture;

Design and maintain clean, well-modeled datasets and analytics layers that enable business stakeholders to answer their own questions with confidence;

Own data quality, documentation and reliability for the analytics products and pipelines you build, with a bias toward self-service and scalability;

Stay current on advancements in AI and analytics technologies, and proactively identify opportunities to apply them to financial services workflows


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