Data Engineering Consultant - Databricks (Remote)

At our core, we help organizations unlock the full value of their data - turning complexity into clarity and strategy into measurable outcomes. As a Data Vault Engineer, you will support the delivery of data solutions and contribute to client transformation initiatives.

This role focuses on building on foundational experience at the intersection of data engineering, analytics, and consulting delivery. You will work alongside experienced team members to help design, develop, and implement modern, cloud-based data solutions that enable efficient analytics and data-driven decision-making.

You will support development efforts across platforms such as Snowflake, Databricks, AWS, and Azure, contributing to client data modernization initiatives. You will assist in translating business and technical requirements into well-structured data solutions while developing your technical and consulting skill set.

Success in this role requires strong problem-solving abilities, attention to detail, and a willingness to learn in a fast-paced environment. You will be expected to contribute to team deliverables, continuously build technical expertise, and support high-quality client outcomes.

 

What You'll Work On

• Support client engagements as a contributing project team member
• Assist in gathering and understanding business and technical requirements
• Translate requirements into technical tasks under guidance from senior team members
• Support preparation of presentations, documentation, and deliverables
• Develop and support data solutions leveraging:
• Snowflake (data warehousing, data storage)
• Databricks (data processing, Spark workloads)
• AWS ecosystem (S3, Glue, Redshift, Lambda, EMR, IAM)
• Microsoft Fabric / Azure (Synapse, ADF)
• DataVault Data Automation
• Build and maintain data pipelines (primarily batch, with exposure to near real-time)
• ETL/ELT development and data integration processes
• Contribute to development of data platforms including data lakes and data warehouses
• Follow established best practices for coding, testing, and performance optimization
• Support senior team members in troubleshooting and resolving data issues
• Participate in code reviews, testing, and quality assurance activities
• Manage assigned tasks and deliver them within project timelines with minimal oversight
• Assist with analytics and reporting by preparing curated datasets
• Support advanced analytics initiatives such as machine learning data preparation
• Stay current with tools, technologies, and best practices through continuous learning
• Support data governance, data quality, and documentation efforts
• Follow data security and compliance standards
• Contribute to maintaining metadata, lineage, and technical documentation

 

What You'll Bring

• Bachelor’s degree in Data Analytics, Business Analytics, Information Systems, Computer Science, Statistics, Mathematics, Economics, or related field
• 3-5 years of experience in data engineering, analytics, or related technical roles
• Foundational experience with:
• SQL and basic data modeling concepts
• ETL/ELT processes and data integration

• Exposure to cloud platforms such as AWS, Azure, or GCP

• Familiarity with tools such as Snowflake, Databricks, or similar platforms is a plus
• Exposure to programming languages such as Python or Scala is preferred
• Basic understanding of modern data architecture concepts (data lakes, warehouses)
• Exposure to data visualization tools (e.g., Power BI, Tableau) is a plus
• Strong analytical and problem-solving skills

 

How You Work

• Need to be proactive and look for ways to pitch in
• Someone who is customer oriented and quality driven
• Much be able to handle multiple priorities and have good time management
• This is an ever-changing landscape so the ability to be flexible with routines is important
• Thinking outside the box to find better ways of working to deliver for clients and internally

 

Bonus Points If You Have

• Datavault Experience - VaultSpeed, DataVault Builder, Wherescape
• High attention to detail and commitment to quality
• Effective communication and teamwork skills
• Ability to learn quickly and adapt in a consulting-driven, fast-paced environment
• Demonstrated curiosity and interest in data engineering, analytics, and emerging technologies

 

What Success Looks Like

• Quick to develop strong client relationships
• Assist leadership with growing business
• Identifying new ways to contribute
• Become invaluable to clients
• Is a go to person for leadership to develop and deliver
• Working in a collaborative environment and supporting those around them