Data vault data engineer Lead

Job Title:Data Vault Data Engineer Lead

Type:Contract (13 years of experience)

Location: Atlanta, GA or Encinitas, CA

Roles and Responsibilities

Data Vault Architecture and Design

• Lead the design and implementation of Data Vault 2.0 architecture to support enterprise data warehousing solutions.
• Define and standardize Data Vault components, including hubs, links, and satellites, ensuring scalability, auditability, and alignment with business requirements.
• Develop and optimize raw vault and business vault layers to meet performance and agility needs.

Data Integration and Engineering

• Oversee the ingestion, transformation, and modeling of data from various structured and unstructured sources into the Data Vault.
• Implement ETL/ELT processes using industry-standard tools (e.g., Talend, Azure Data Factory, Informatica, dbt, or Snowflake Streams).
• Ensure robust data quality and governance standards across data pipelines and integration workflows.

Leadership and Team Collaboration

• Act as the technical lead for a team of data engineers, providing guidance on Data Vault best practices and performance tuning.
• Collaborate with business stakeholders, data architects, and analysts to translate requirements into actionable data models and solutions.
• Provide mentorship to junior engineers, conducting code reviews and ensuring adherence to best practices.

Project Management and Delivery

• Manage and prioritize tasks for the team, ensuring project deliverables are on time and meet quality standards.
• Provide detailed documentation, including data lineage, process flows, and metadata management.
• Proactively address risks, troubleshoot issues, and ensure alignment with organizational goals.

Innovation and Optimization

• Stay updated with emerging data engineering technologies and techniques, proposing improvements to enhance system performance and efficiency.
• Implement automation strategies for data pipeline processes to improve reliability and reduce manual effort.
• Optimize storage and query performance in cloud-based data platforms such as Snowflake, AWS, or Azure.

Compliance and Governance

• Ensure compliance with data privacy regulations and internal governance policies.
• Establish robust monitoring, auditing, and logging frameworks for data operations.

Required Qualifications

Experience

• 13 years of experience in data engineering and enterprise data warehousing.
• 5 years of hands-on experience with Data Vault 2.0 methodology and implementation.
• Proven experience in designing and deploying data solutions on cloud platforms like AWS, Azure, GCP, or Snowflake.

Technical Skills

• Proficiency in SQL, Python, and ETL/ELT tools (e.g., Talend, Informatica, Azure Data Factory).
• Strong knowledge of data modeling tools (e.g., Erwin, dbt, PowerDesigner).
• Expertise in cloud-based data warehouses (e.g., Snowflake, Redshift, or BigQuery).
• Version control using Git or equivalent tools.

Soft Skills

• Excellent leadership and mentoring abilities.
• Strong communication and collaboration skills with both technical and non-technical stakeholders.
• Ability to work independently and manage contract-based deliverables effectively.

Certifications (Preferred)

• Data Vault 2.0 Certification
• Certifications in Snowflake, AWS, or Azure