Data Warehouse Engineer

Mitchell Martin Inc, a forty-year-old, privately owned, technology-focused, staffing company where data is central to how we understand, run, and transform our business. We run a centralized data team that serves the entire organization, both delivering analytics and operating business-critical data and software pipelines that directly affect the lives of our consultants. This role takes over the engineering half of that team and, by virtue of our size, is a multi-faceted position spanning the responsibilities of software engineer, data engineer, and analytics engineer. The platform is focused on Python assets orchestrated with Dagster.

The successful candidate will continue to enable the synthesis of data across the organization's different departments and tools, creating a single unified data platform. You will evolve fundamental systems, procedures, and reporting infrastructure that make moving up the data pyramid into higher-level initiatives (such as data science and machine learning) possible.

Responsibilities:

• Design, build, and maintain Python-based data assets orchestrated with Dagster, covering ingestion, transformation, and loading across internal and external data sources
• Develop and maintain dbt models to support clean, tested, and documented data transformations within the warehouse
• Build and maintain integrations with third-party APIs and vendor systems to construct reliable data pipelines
• Implement best practices to standardize and improve the integrity and reliability of extraction, transformation, loading, and storage processes, including:
• Organizing and versioning code in GitHub, with appropriate branching, protection, and PR review practices
• Logging and monitoring
• Alerting for failed or degraded pipelines
• Design and maintain data models and schemas within Snowflake, applying sound RBAC and access-control practices
• Organize and automate tasks and infrastructure on AWS
• Partner with both technical and non-technical stakeholders across departments to understand data needs and translate them into pipelines, models, and reports
• Participate in the evaluation and integration of new tools and products that support the firm's business processes
• Contribute to the long-term evolution of the data platform as the team takes on higher-level initiatives such as data science and machine learning

Skills:

• Strong problem-solving and project-management skills, with the ability to work independently on a small, high leverage team
• Desire to understand and maintain established data assets, while critically thinking about improvements and new implementations
• Excellent communication and interpersonal skills, with comfort translating between technical and non-technical audiences
• Exemplary analytical skills

Experience:

• Intermediate to advanced Python, including object-oriented programming, dataclasses, and exception handling; experience with async programming is a plus
• Experience working with third-party APIs and vendors to build data pipelines
• Intermediate to advanced SQL, including CTEs, window functions, and recursive queries
• Experience with dbt
• Experience with Dagster (or comparable orchestration tools such as Airflow)
• Working knowledge of Snowflake or an equivalent cloud data warehouse, including RBAC, data loading, and data modeling
• Basic AWS knowledge, particularly IAM and S3
• Basic HTML and CSS
• Basic Excel, including sorting and filtering
• Basic GitHub, including branching, branch protection, merging, pull requests, and secrets/actions

Education/Training:

• Degree in Computer Science or related field or similar experience

Work Environment – Must be willing and able to commute to New York City up to 4 days a week

Core Technologies

Python | SQL | Snowflake | Dagster | DBT | Data Modeling | API Integration

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