Cloud Data Engineer – Consulting

The Planet Group; Richmond (VA); On-site; USD 69,000 - 110,000; Full time

Job summary

The Planet Group has partnered with a Richmond, VA based company to recruit Cloud Data Engineers to join a growing consulting team supporting enterprise data initiatives. You will design and deliver modern cloud data solutions across client engagements, industries, and tech stacks.

Ideal candidates bring hands-on data engineering experience, strong SQL skills, and the ability to communicate technical options clearly to stakeholders.

Qualifications

• 2+ years of professional Data Engineering experience with ownership of deliverables.
• Hands-on with SQL and data transformation, and experience with at least one major cloud ecosystem (AWS or Azure).
• Able to translate business requirements into scalable data solutions.

Responsibilities

• Design, develop, enhance, and support production-grade data pipelines.
• Build scalable data solutions in AWS, Azure, and other cloud environments.
• Translate business requirements into effective data solutions for clients.
• Develop ETL/ELT processes for ingestion, transformation, cleansing, and delivery of enterprise data.
• Contribute to lakehouse architectures with Bronze, Silver, and Gold patterns.
• Design and support event-driven data processing solutions.
• Evaluate architectural options based on scalability, performance, cost, and business needs.

Skills

SQL

AWS

Azure

ETL/ELT

Lakehouse Architecture

AI-assisted development

Job description

Pay rate: $50-$80/hour (depending on experience)

The Planet Group has partnered with a Richmond, VA based company to locate Cloud Data Engineers to join a growing consulting team supporting complex data initiatives for enterprise organizations. These are long term roles offering the opportunity to work across a variety of client engagements, industries, and technology environments over the course of your career with the firm.

You’ll contribute to the design and delivery of modern cloud-based data solutions while working directly with clients to solve challenging business and technical problems. The right person will combine strong hands-on engineering skills with the ability to understand business needs, evaluate technical options, and communicate recommendations clearly.

This opportunity is best suited for someone who considers themselves a well-rounded data engineer rather than a specialist in one particular tool or platform.

Candidates should live within 50 miles of Richmond, VA

What You’ll Do

• Design, develop, enhance, and support production-grade data pipelines and data processing solutions.
• Build scalable data solutions within modern AWS, Azure, and other cloud environments.
• Work with clients and internal technical teams to understand business requirements and translate them into effective data solutions.
• Develop ETL/ELT processes supporting ingestion, transformation, cleansing, and delivery of enterprise data.
• Contribute to modern lakehouse and layered data architectures, including Bronze, Silver, and Gold patterns.
• Design and support event-driven data processing solutions.
• Evaluate technical approaches and explain architectural tradeoffs based on scalability, performance, cost, and business requirements.
• Move between client engagements over time, adapting to new business domains, technologies, and technical challenges.
• Use modern AI and AI-assisted development capabilities to improve engineering productivity and solution delivery.
• Collaborate with engineers, architects, business stakeholders, and client teams throughout the project lifecycle.

What We’re Looking For

• 2+ years of professional Data Engineering experience with demonstrated ownership of technical deliverables.
• Experience with several of the following:
• Architecture: Lakehouse, Medallion Architecture, event-driven processing, cloud migration
• Development: SQL, data transformation frameworks, AI-assisted development tools
• You do not need experience with every technology listed. Breadth, adaptability, and the ability to learn new environments are more important than checking every box.
• Hands-on experience developing and supporting production data pipelines.
• Strong SQL skills and experience working with enterprise databases and data platforms.
• Experience with at least one major cloud ecosystem, with AWS and/or Microsoft Azure strongly preferred.
• Knowledge of modern data engineering, ETL/ELT, and data transformation patterns.
• Experience working with large or complex enterprise data environments.
• Understanding of modern data architecture concepts, including lakehouse and Medallion Architecture approaches.
• Exposure to event-driven data processing or streaming architectures.
• Experience using AI or AI-assisted development tools as part of the software or data engineering lifecycle.
• Ability to discuss technical architecture and recommend solutions based on both technical and business considerations.
• Strong communication skills and confidence working directly with clients and stakeholders.
• An adaptable, curious approach to technology and an interest in continually learning new platforms and techniques.