Data & Analytics Engineer

DeleteMe

1d•$100,000 - $100,000

About The Position

This position is a key partner across the organization, sitting within the Data Warehouse team to bridge the gap between raw data engineering and business strategy. The Data & Analytics Engineer is responsible for designing, building, and optimizing scalable data models in Snowflake using dbt, ensuring data integrity and high performance. This role balances technical warehouse architecture with the ability to translate complex business requirements into actionable data products.

Requirements

Mastery of complex SQL, including window functions, CTEs, and performance tuning for large-scale datasets.
Proven experience building production-grade dbt projects, including macros, seeds, and testing suites.
Strong understanding of Snowflake-specific features such as clustering, virtual warehouses, and zero-copy cloning.
Deep knowledge of dimensional modeling, fact/dimension design, and data warehousing principles.
Availability in US Eastern (EST) hours.
Ability to understand organizational drivers and communicate technical details effectively to non-technical stakeholders.
Strong problem-solving skills with the ability to identify root causes in data discrepancies or performance bottlenecks.

Nice To Haves

Experience with Python for data scripting or automation.
Familiarity with data observability tools (e.g., Monte Carlo, Elementary).
Experience in a high-growth startup environment.
Cybersecurity experience

Responsibilities

Data Modeling & Development: Architect and maintain robust, modular data models in Snowflake using dbt, following industry-standard modeling methodologies (e.g., Kimball).
Warehouse Optimization: Write and tune advanced SQL to ensure optimal query performance, cost-efficiency, and resource management within the Snowflake environment.
Data Observability & Quality: Implement and manage automated testing, monitoring, and alerting frameworks to ensure data accuracy, freshness, and lineage.
Stakeholder Collaboration: Partner with business units to define KPIs, capture requirements, and translate business logic into technical data specifications.
End-to-End Delivery: Own the full data lifecycle from ingestion to production-grade data marts and strategic BI visualizations and dashboard building.
Engineering Excellence: Apply software engineering best practices to data development, including version control (Git), CI/CD, and detailed technical documentation.
Process Improvement: Continuous refactoring of legacy code and data structures to improve maintainability and scalability of the analytics stack.

Benefits

Comprehensive health benefits - Medical, Vision, Dental
Flexible work schedule
Generous 401k matching up to 6%
20 days paid time off
15 sick days
12 company-paid holidays
Childcare expense reimbursement
Fitness and cell phone reimbursement
Birthday time off
Competitive salary - We publish salary ranges to promote transparency and ensure fair compensation. Final offers are based on skills, experience, and internal equity.
This role may require occasional domestic and international travel. All standard travel expenses will be covered in accordance with the company's travel reimbursement policy.