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Job Summary:
Medix is seeking a highly motivated, hands-on, and analytical Lead Data Engineer to lead our data infrastructure and empower our Business Intelligence and Analytics teams. The ideal candidate will be a player-coach, combining leadership and mentoring with deep technical expertise in designing, implementing, and optimizing data solutions using our modern data stack. This role is responsible for the full lifecycle of our data, from ingestion and transformation to modeling and delivery, ensuring the accuracy, reliability, and performance of our data assets.
Key Responsibilities:
Individual Contribution (IC):
Architect & Build Data Pipelines: Design,construct, and maintain highly scalable and reliable data pipelines using Fivetran, custom Python scripts, and dbt to ingest data from various source systems, including Hubspot, Bullhorn (RDS SQL Server), and other third-party APIs.
Optimize Snowflake: Develop, manage, and optimize our Snowflake data platform, ensuring best practices in data warehousing, performance, and cost management.
Fortify Data Security: Implement and enforce data security best practices across the data stack, including the configuration and management of Snowflake security features like Role-Based Access Control (RBAC) and integration with Single Sign-On (SSO).
Craft Data Models: Create and maintain complex data models in dbt for use in business analysis, Tableau reporting, and other data-driven applications.
Develop Python-based Integrations: Build and maintain Python-based data pipelines to consume data from various APIs, ensuring robust error handling and scalability.
Troubleshoot & Automate: Proactively troubleshoot and resolve issues within the data warehouse and production environments, implementing automation where possible.
Ensure Data Governance: Develop and maintain comprehensive data architecture diagrams, data dictionaries, and a data catalog to ensure data quality and discoverability.
Leadership & Collaboration:
Mentor an Analytics Engineer: Oversee and mentor one Analytics Engineer, providing guidance on best practices, technical skills development, and project execution.
Cross-Functional Partnership: Collaborate with Business Intelligence, Analytics, Product, and IT teams to gather business requirements and translate them into effective data solutions.
Provide Data Insights: Support all levels of the organization with ad-hoc data requests, ensuring the delivery of consistent, timely, and accurate information.
Build Relationships: Establish and maintain strong relationships with key stakeholders and teammates.
Key Relationships:
Reports to: VP, Business Analytics
Direct Reports: Analytics Engineer
Close Collaboration with: Business Intelligence, Analytics, Product, and IT
Qualifications:
Required Technical Skills:
Proficiency in our core data stack: Fivetran, Snowflake, and dbt.
Strong experience with SQL for complex querying, data manipulation, and performance tuning.
Demonstrated experience in developing and maintaining data pipelines using Python to consume data from APIs.
Experience with Microsoft SQL Server, particularly in an AWS RDS environment.
Experience:
Bachelor’s degree in Computer Science, Data Science, Software Engineering, Information Technology, Management Information Systems (MIS), Data Analytics, or a related field.
Minimum of 4+ years of experience in data engineering, data architecture, or a similar role.
Proven experience in designing and implementing ELT/ETL data pipelines and developing robust data models.
Experience with version control systems (e.g., Git/GitHub) is required.
Preferred Skills & Attributes:
A detailed-oriented, curious, and proactive problem-solver.
Self-motivated with excellent communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.
Ability to work effectively with diverse stakeholders, from developers to executive leadership.