Analytics Engineer

Analytics Engineer (Sepulveda Finance)

This position is remote, and it is eligible for the 9/80 flex schedule. The pay range for this position is $99,855 - $110,950 annually.

About Didi Hirsch

Didi Hirsch Mental Health Services has been a national leader in whole-person mental health, crisis care, and substance use services since 1942 and is home to the nation’s first Suicide Prevention Center. We are a nonprofit organization providing care to nearly 200,000 people annually across our programs. Didi Hirsch has deep roots in community-based mental health and a commitment to providing culturally responsive services that are just and equitable.

As an organization, we value equity, diversity, and inclusion. More than 1,000 dedicated employees and volunteers make Didi Hirsch’s work possible. We intentionally recruit and retain a workforce that is reflective of the communities we serve and strive to cultivate a sense of belonging for them. We embrace employees and candidates from all backgrounds who want to help make this vision a reality.

Summary

Under the general supervision of the Director of Corporate Reporting, the Analytics Engineer will be responsible for delivering well-defined, transformed, tested, documented, and code-reviewed analytic data sets to meet the needs of departmental and agency staff. They are responsible for building the foundational layer for dashboards and self-service reporting. They will employ best practices like version control and continuous integration to the analytics code base and ensure data quality and accuracy. They will work collaboratively with IT to design and construct data pipelines and develop tools/processes to expand the data capacity of the department and streamline/automate processes. Works with end users to design the data warehouse for analysis and manages its maintenance.

Primary Duties

1. Expand our data warehouse with clean data ready for analysis.
2. Help to define and improve our internal standards for style, maintainability, and best practices for a high-scale data infrastructure.
3. Data modeling: Model raw data into clean, tested, and reusable datasets. Build visual representations of data and communicate connections between different information points and structures. Define the rules and requirements for the formats and attributes of data.
4. Data transformation: Apply various transformations to different data pieces to ensure they correspond to given tasks and effectively support analytic purposes.
5. Maintain data documentation & definitions: Ensure the internal team is using consistent and clear definitions and language.
6. Define data quality rules, standards, and metrics: Define metrics to be used and measures to be taken to guarantee data is accurate enough to fit operational and analytics needs.
7. Apply best practices to analytics code (e.g., version control, testing, continuous integration).
8. Data visualization: Convert data into a suitable graphic format by building dashboards, graphs, charts, and reports using Business Intelligence tools.
9. Close collaboration with internal Finance/Billing team members to align reporting requirements with data assets.
10. Collaborate across multiple departments (e.g. IT, Clinical Operations, etc.) to understand business needs, analyze complex data, provide advanced data analysis and reporting, and clearly communicate recommendations.
11. Train stakeholders (data users) on how to use data visualization tools.

1. At least a bachelor’s (master’s preferred) degree in technical/data-oriented fields (e.g., statistics, mathematics, computer science, software engineering, or IT).
2. 2 or more years of experience working in data-driven landscapes where data is used to solve business/operational needs, preferably in a healthcare setting.
3. Strong SQL skills, specifically in creating logic for data transformations, writing queries, and building data models.
4. Experienced in programming languages such as R and Python.
5. Knowledge of software engineering best practices (e.g., version control, testing, continuous integration).
6. Experienced with Git or other version control systems.
7. Experience with tools to build data pipelines.
8. Experience with dashboard tools such as PowerBI, Tableau, etc.
9. Interpersonal and communication skills.
10. The ability to present ideas, information, and viewpoints clearly, both verbally and in writing.
11. A commitment to team objectives and Didi Hirsch philosophies.
12. Ability to adapt to changing needs by acquiring new skills and knowledge.
13. Current California driver’s license, car insurance, and a driving record acceptable to the Agency’s insurance carrier.