Data Engineer

Conduct in-depth exploratory data analysis to uncover trends and patterns in structured and unstructured datasets.

Translate complex business requirements into robust data solutions, integrating insights from diverse non-ERP sources with our Enterprise Data Warehouse (EDW).

Design, build, and optimize scalable ELT/ETL pipelines to ingest, transform, and publish data into the Snowflake Data Cloud.

Develop and maintain high-quality, analytics-ready data models using dbt, emphasizing modular design, reusability, rigorous testing, and maintainability.

Design and implement a reusable semantic layer that adheres to architectural standards and supports various consumption patterns (AI, agentic solutions, dashboards).

Leverage Snowflake Cortex to integrate AI/LLM capabilities directly into data pipelines, enabling advanced analytics.

Design and develop data consumption layers, including dashboards, reports, conversational analytics, and agentic solutions.

Champion and enforce data quality, observability, lineage, governance, and access control standards across our AI-ready data architecture.

Applies working knowledge of databases, relational databases, cloud services, and scripting languages

Contributes to data quality and compliance, including cleansing and scrubbing of data, data integrations and data quality framework

Collaborate strategically with data architects, analysts, and business stakeholders to define long-term data strategies and deliver scalable, reliable data solutions.

Establish and enforce technical governance, CI/CD best practices, and rigorous version control to ensure the integrity, security, and scalability of our modern data stack.

Demonstrated experience applying Agile, Scrum, or Kanban methodologies within a data engineering environment.

• A self-starter with proven expertise to deliver outcomes with minimal supervision