Data Engineer
Career Opportunities
Job Type
Full-time
- Outward Mindset - foundation of our culture, which influences the right behaviors, that leads to results
- Entrepreneurial - the ability to get things done with resources you don't control
- Humility - deep comfort in knowing when you don't know and asking questions
- Collaboration - we always give benefit of doubt that each person has something to contribute
- ELT Architecture: Design and build robust, scalable ELT pipelines to ingest data from various sources (APIs, production databases, third-party tools) into Snowflake.
- Data Transformation (dbt) : Own the dbt project structure. specific responsibilities include:
- Developing complex SQL-based data models (incremental models, snapshots).
- Writing Jinja macros to keep code DRY (Don't Repeat Yourself).
- Implementing data quality tests (schema tests, custom data tests).
- Snowflake Optimization: Manage the Snowflake environment to ensure cost-efficiency and performance. This includes warehouse sizing, clustering strategies, and utilizing features like Snowpipe and Zero-Copy Cloning.
- Data Quality & Governance: Champion data integrity. Implement observability tools and alerts to catch pipeline failures or data anomalies before they reach the business users.
- Mentorship : Act as a technical lead for junior engineers, conducting code reviews, and establishing best practices for SQL and version control.
- Collaboration: Translate business requirements from Product and Analytics teams into technical specifications and data models
- Required education: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience).
- Required industry experience or certification:
- 3+ years of professional experience in Data Engineering and Database Development with medical and prescription claims
- Specific Stack Experience:
- 2+ years of hands-on experience specifically with Snowflake (architecture, snowpipe, streams/tasks, and security).
- 1+ years of production experience with dbt (developing packages, macros, and incremental models).
- SQL Mastery: Expert-level SQL skills with the ability to write complex, highly optimized queries. You can write complex, performant queries and debug spaghetti code with ease. Deeply familiar with Snowflake architecture, including separation of storage and compute, semi-structured data handling (JSON/Variant), and security management (RBAC).
- Programming: Proficiency in Python for scripting, custom connectors, or orchestration tasks.
- Orchestration: Experience with workflow orchestration tools (e.g., Airflow or FiveTran, dbt or dbt Cloud).
- Version Control: Strong familiarity with Git flows and CI/CD pipelines for data (e.g., GitHub Actions, GitLab CI).
- dbt Proficiency: Strong experience with dbt (Core or Cloud). You understand the difference between ephemeral, table, and view materializations and know how to use dbt for documentation and lineage.
- Data Governance principles and best practices
- Master Data Management principles and best practices
- Experience with database management
- Experience handling healthcare data formats (e.g. Pharmacy Claims data, Eligibility data, Medical Claims data, etc.).
- Knowledge of Azure/GCP services or similar AWS core services (S3, Lambda, IAM).
- Experience migrating legacy stored procedures to modern dbt models.
- Python: Proficient in Python for scripting, API interaction and Streamlit apps
- Version Control: Strong understanding of Git workflows (branching, merging, pull requests) specifically within a data context.
- Ability to work well with others in a collaborative environment
- Ability to get things done with resources you don't control
- Willingness to admit you don't know and ask for help
- Exhibit constant curiosity and a drive to problem solve
- Exhibit desire to learn and grow on a continuous basis
Vacancy posted 5 days ago
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