Data Vault Engineer - VaultSpeed / Snowflake / 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.