Data Modeler

Role: Lead AWS Data Engineer with Semantic Data Modeling

Location: Anywhere in USA (100% Remote)

Duration: 12+ Months

Must have: Public Trust Clearance

Data Analytics is looking for Data Product Engineer to help build cloud-based Data Products

Position Responsibilities:

Design and implement semantic models that facilitate data understanding and usage across various business functions.

Collaborate with cross-functional teams to gather requirements and translate business needs into effective data models.

Utilize AWS services, particularly Data Zone, to build and manage data pipelines and semantic layers.

Leverage ontology tools such as dbt products, QuickSight, AtScale, and DataWalk to enhance data visualization and reporting capabilities.

Develop and maintain a metric store with knowledge graph capabilities to ensure data quality and enable data lineage as part of data governance.

Create and maintain data models for data lake house architecture, ensuring alignment with best practices in data governance and quality.

Conduct data analysis and provide insights to support decision-making processes within the organization.

Stay updated with industry trends and emerging technologies related to data modeling and semantic layers.

Employer will not sponsor applicants for employment visa status.

Basic Qualifications (Required Skills/Experience):

• 8+ years of experience as a data engineer. Strong understanding of Semantic Modeling, Data Products, and datalake.
• Proven experience in data modeling, particularly for semantic layers in a business-facing role.
• Strong understanding of data products and their applications within a data lake house architecture.
• Experience in developing a metric store with knowledge graph capabilities to enhance data quality and lineage.
• Excellent communication skills, with the ability to convey complex data concepts to non-technical stakeholders.
• Strong analytical and problem-solving skills, with a focus on delivering actionable insights.

Mandatory Skills:

• Hands-on experience with AWS, specifically in implementing Data Zone and related services.
• Handson experience with any ontology tools such as dbt Labs, QuickSight, AtScale, or DataWalk.

Typical Education & Experience:

• Education/experience typically acquired through advanced education (e.g. Bachelor) and typically 8 -10 years'' related work experience or an equivalent combination of education and experience (e.g. Master 8 years'' related work experience.)