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# Data Engineer/Snowflake/AI

- **Company:** Intersources Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, ARM Architecture, Microsoft Azure, Big Data, Computer Programming, Data Architecture, Information Engineering, Data Systems, Data Warehousing, Database Applications, Fault Tolerance, R (Programming Language), Iterative and Incremental Development, Python (Programming Language), Machine Learning, NoSQL, Software Engineering, SQL Databases, Systems Architecture, Web Platforms, GitHub Copilot, Snowflake, Data Strategy, Information Technology, Apache Kafka, Data Management, Data Pipelines, Databricks
- **Published:** June 25, 2026
- **Apply:** https://www2.jobdiva.com/portal/?a=62jdnw10t7d77ytz0lbaey9qxonk3b05a9tqw96rb7z6hlfo7xj79l9g6mp6aj2o&compid=0/jobs/32494339#/jobs/32494339

## About the Role

**** CANDIDATES MUST BE SENIOR SNOWFLAKE DATA ENGINEERS WITH EXPERIENCE WORKING WITH ai AND HAVE EXCELLENT COMMUNICATION SKILLS/NO ACCENT., Bachelor's or equivalent. Master's Degree in Computer Science, Engineering, or Management of Info Systems/Technology preferred
Advanced Education in Statistics or Mathematics would be a plus
3+ years building data warehouses using Snowflake
Experience using Snowflake tools like Snowpipe and Snowpark
2+ years of experience using DBT to build data pipelines
3+ years of experience in developing BigData and/or machine learning solutions
3+ Years of experience defining and/or designing data architectures
1+ years using AI development tools such as Github Copilot, Claude Code and others, Demonstrated enthusiasm for leveraging AI technologies to enhance productivity and effectiveness in data engineering workflows
Hands-on experience with cloud platforms such as Microsoft Azure and/or Amazon Web Services (AWS)
Strong proficiency in SQL, NoSQL, Big Data, and graph technologies, along with programming experience in languages and tools such as Python, R, Kafka, and Storm
Solid background in Agile software development methodologies, including experience with Scaled Agile Frameworks (SAFe)
Proven coding expertise, with the ability to rapidly develop and prototype solutions
Strategic mindset with the ability to conceptualize and deliver innovative digital products while effectively managing multiple competing priorities
Results-oriented approach with a bias for action, embracing iterative development and continuous improvement
Experience collaborating with and/or managing both internal and external teams across multiple brands and digital platforms of varying maturity levels
Strong interpersonal and communication skills, with the ability to effectively partner with non-technical stakeholders, reconcile differing objectives, and align teams around unified
solutions
Demonstrated ability to manage multiple projects simultaneously, adapt to shifting priorities, and deliver under dynamic conditions
Proven ability to influence stakeholders, drive organizational change, and implement standardized processes within complex business environments
Passion for data and a commitment to continuous professional growth and development
Excellent written and verbal communication skills
Collaborative team player with a proactive mindset, willing to support others and seek input when needed
Ability to translate business and user needs into practical, scalable technical solutions

## Description

Join a high-performing Data Engineering team responsible for managing and optimizing both internal and external data sources, and for designing and building modern data warehouses. The team leverages leading technologies including Microsoft Azure and AWS cloud platforms, Databricks and Snowflake, and a robust ecosystem of tools such as Fivetran, Hightouch, DBT and Alation. Candidates must be strong emphasis is placed on the adoption of emerging AI technologies to enhance development efficiency and analytical capabilities. This includes tools such as Snowflake Cortex, Databricks Genie, GitHub Copilot, and Claude Code among others. The ideal candidate will be comfortable integrating AI into their workflow to accelerate the development of scalable data pipelines and analytics solutions., Join a high-performing Data Engineering team responsible for managing and optimizing both internal and external data sources, and for designing and building modern data warehouses. The team leverages leading technologies including Microsoft Azure and AWS cloud platforms, Databricks and Snowflake, and a robust ecosystem of tools such as Fivetran, Hightouch, DBT and Alation.

A strong emphasis is placed on the adoption of emerging AI technologies to enhance development efficiency and analytical capabilities. This includes tools such as Snowflake Cortex, Databricks Genie, GitHub Copilot, and Claude Code among others. The ideal candidate will be comfortable integrating AI into their workflow to accelerate the development of scalable data pipelines and analytics solutions.

This role requires a highly results-driven individual who thrives in a dynamic, fast-paced environment. The position demands versatility, initiative, and a proactive mindset. You will regularly collaborate with business stakeholders to translate requirements into actionable data solutions and insights, as well as partner with external vendors to ensure alignment and successful delivery.

Success in this role requires strong adaptability, the ability to quickly learn new technologies, and comfort navigating evolving priorities. The environment is fast-moving, and candidates must be able to think critically, respond to change, and continuously upskill-particularly as AI capabilities rapidly evolve.

As a member of the Data Engineering team, you will be expected not only to leverage AI tools effectively, but also to remain agile as these technologies advance. Responsibilities will include developing data pipelines, as well as contributing to lightweight front-end solutions that enable business users to perform reporting and analytics.

You will play a key role in supporting the organization's growth objectives by managing multiple initiatives simultaneously, contributing both independently and collaboratively across business and technical teams. The ideal candidate combines strategic thinking with hands-on execution, demonstrating an entrepreneurial mindset and a strong sense of ownership.

We are seeking a passionate data professional who embraces challenges and is committed to delivering high-quality solutions that drive value for internal stakeholders, while fostering a positive and collaborative team environment.

This position reports to the Data Engineering Team Lead.

Major Responsibilities

Design, build, and maintain scalable, fault-tolerant batch and real-time data pipelines to support internal applications, operational workflows, and business intelligence platforms

Leverage and advance AI-driven capabilities to enhance data pipeline development, deployment efficiency, and analytical insights

Translate business requirements into high-impact data solutions that deliver value to both internal stakeholders and end users

Collaborate closely with cross-functional partners to ensure requirements are clearly defined and successfully delivered; actively engage with end-user communities to gather feedback, address concerns, and recommend improvements

Demonstrate strong technical expertise while contributing to the evolution of overall data and system architecture

Support the implementation and adoption of the Enterprise Data Architecture, ensuring alignment across functional teams including Data Strategy, Marketing, Finance, HR, and others

Provide technical guidance and insights during the design and development of complex, high-impact machine learning and data-driven applications across multiple business domains

Ensure solutions align with enterprise architecture standards and effectively utilize approved enterprise platforms and tools

Apply Agile methodologies, developing and delivering solutions in alignment with prioritized business needs and sprint objectives

Develop and maintain data-driven applications that enable seamless integration with partners and external systems

Establish and promote best practices for data management, quality, and governance across the organization

Drive continuous improvement of deliverables, development standards, and Software Development Life Cycle (SDLC) processes


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