Lead Data Engineer with Semantic Data Modeling

Role- Lead Data Engineer with Semantic Data Modeling
Location- 100% Remote
Exp Required- 11+ Years

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.)