Senior Data Analytics Engineer

PsychPlus is on a mission to transform mental health care delivery by offering a digital-first, modern approach to psychiatry and therapy. With a presence both in-person across Texas and virtually, we strive to make mental health services accessible and convenient for all. By combining exceptional medical and psychological care with advanced technology, we aim to provide integrated, affordable, and high-quality mental health support. Join us to help ensure that every individual has access to the care they deserve.

Key Responsibilities

- Analytical Data Modelling: Develop customized datasets to support Product, Operations, and Clinical teams. Build and maintain automated reports, analyses, and dashboards to track key product features, ensuring stakeholders have access to accurate and up-to-date data. Define data model grain, keys, relationships, and business logic to create consistent and trusted datasets for reporting and analysis.

- KPI Discovery and Definition: Collaborate with teams to understand their needs and translate them into clearly defined, computable KPIs. Establish each metric’s business meaning, calculation method, data sources, and reporting frequency, then validate and monitor these metrics regularly with stakeholders.

- Technical Leadership and Ownership: Set priorities and acceptance criteria with stakeholders, document architectural decisions, establish modelling and review standards, and mentor team members. Take ownership of investigating and resolving issues related to the reliability, performance, and cost of analytical data products.

- Data Pipelines Framework: Enhance the data pipelines framework to build scalable, reliable, and maintainable pipelines across different data layers (bronze, silver, gold). Promote best practices such as idempotency to ensure pipeline robustness.

- Data Quality Frameworks: Identify and flag data issues like missing fields, incorrect types, or schema mismatches at the source. Develop automated tests and quality checks integrated into pipelines to ensure data completeness and consistency throughout ingestion and processing.

- Define Analytics Tracking: Lead the design and implementation of analytics tracking for in-app events, especially when launching new features such as pages and buttons.

- ML & AI Pipelines: Collaborate with AI Scientists and Engineers to contribute to building machine learning pipelines using Python.

Required Qualifications

- Fluent in English with excellent communication skills.

- Minimum of 6 years’ experience as a Data Engineer, proficient in creating modular, version-controlled data pipelines.

- Strong expertise in Python, particularly PySpark, and SQL.

- At least 4 years of experience working with Microsoft Fabric and/or Databricks.

- Proven experience in building dashboards and semantic models using Power BI, including proficiency in DAX.

- Experience with in-app analytics tracking and A/B testing methodologies to evaluate product changes.

- Background working with healthcare and/or clinical data.

Preferred Qualifications

- Experience within the digital healthcare industry is highly desirable.

- Ability to clearly communicate technical decisions, weighing pros and cons, and tailoring explanations to different audiences.

- A growth mindset with enthusiasm for debugging data pipeline issues, advocating for data quality, and continuously improving code and processes.

PsychPlus offers the opportunity to work at the intersection of healthcare and technology, contributing to innovative solutions that improve patient outcomes and operational efficiency. If you are passionate about leveraging data engineering to make a meaningful impact in mental health care, this role is an excellent fit.