Data and Analytics Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design adaptable and efficient data models that guide LOB teams towards unified sources of truth across various business sectors.

• Utilize SQL, Python, dbt, and Snowflake to construct and uphold data infrastructure for reporting, analysis, and automation purposes.

• Conduct data quality assurance and create automated testing protocols for Snowflake data models.

• Contribute to data governance initiatives, encompassing permissions, data lineage, and data definitions.

• Develop data security measures ensuring models only access permitted data.

• Create semantic data models that allow LOB data to be accessed through natural-language queries using Cortex Analyst.

• Establish and verify metrics, dimensions, and relationships for AI agents.

• Detect and address gaps in data structure, naming, and coverage that may lead to agent failures or incorrect outputs.

• Document playbooks, reusable data model templates, and libraries of semantic models.

• Facilitate technical workshops to enhance the skills of team members.

• Draft semantic view configurations and YAML/Markdown skill files for non-technical analysts.

• Oversee the complete data stack, from source ingestion to the semantic layer, ensuring production reliability and ease of maintenance.

• Collaborate directly with clients, engineers, and AI experts to convert emerging technologies into quantifiable business results.

• Monitor adoption post-launch, identify barriers, and re-engage stakeholders until the data product is dependable and transferred to operational teams.

• Convert business needs into technical specifications and offer actionable insights to leadership.

⛳️ Requirements

• Over 8 years of experience in analytics engineering, data engineering, or a related technical field, with some of it being customer-facing or cross-functional.

• Daily utilization of an AI coding assistant as a primary tool for development.

• Proficient in SQL, capable of writing window functions and complex joins without consulting documentation.

• Experience with dbt.

• Successfully delivered a production data model or pipeline relied upon by non-technical business users.

• Comfortable using Git (PRs, branches, code reviews).

• Proven experience in translating business requirements into technical specifications.

• Advanced SQL skills: CTEs, window functions, incremental pipeline patterns.

• Experience building data infrastructure with large-scale relational datasets.

• Experience in developing and maintaining dbt projects that include testing, documentation, and CI/CD pipelines.

• Modern, type-hinted, and easy-to-read Python; knowledgeable about Python-based data pipelines and automation workflows.

• Daily use of an LLM coding assistant such as CoCo, Cursor, GitHub Copilot, Claude, or similar tools.

• Ability to create semantic view configurations or structured skill files that address edge cases and demonstrate domain knowledge.

• Strong client-facing communication skills.

• Familiarity with Snowflake Cortex, including Cortex Analyst, Cortex Agents, Cortex Search, semantic views, and Dynamic Tables.

• Experience with Airflow or other orchestration frameworks is a significant advantage.

• Knowledge of enterprise business systems like ERP, CRM, or HRIS is a considerable plus.

• Must be eligible to work without H1B visa sponsorship.

🏝️ Benefits

• Comprehensive health benefits package.

• Opportunities for professional development and training.

• Flexible working hours and remote work options.

• Collaborative and inclusive work environment.