Data Engineer - Remote

Overview

Company Summary

If you are searching for a fulfilling place to develop your career and an opportunity to make a difference in helping others, then keep reading on. Here at AAC, we have a progressive culture; we listen to your ideas, value a work/life balance, invest in education, and we foster trust and respect for all individuals. Our exceptional comp and strong benefits include company matching 401K, medical, dental, vision and life insurance. We are looking for our future leaders, who are not only going to fill the qualifications for this job description, but who are going to exceed expectations. Be a part of a team whose mission is to provide quality, compassionate, and innovative care to adults struggling with addiction and co-occurring mental health disorders. Our purpose and passion are to empower patients, their families, and our communities by helping individuals achieve recovery and optimal wellness of the mind, body, and spirit.

Responsibilities

Introduction: Driving Impact Through Data

As our Data Engineer, you'll be the architect behind our data flow, building the foundational pipelines that turn raw data into actionable intelligence. Your expertise in managing complex data transfers, automating ETL processes, and seamlessly integrating with both on-premise SQL databases and cutting-edge cloud solutions like Salesforce Data Cloud, Google BigQuery, and MuleSoft will be paramount. You'll ensure our data is clean, accessible, and reliable, empowering our analysts and business leaders to make truly data-driven decisions that enhance care delivery and operational efficiency. If you're passionate about the power of data to drive real-world impact in a meaningful industry, this role offers a unique chance to make a significant contribution.

 

The Opportunity:

We are looking for a Data Engineer with a strong focus on data transfer, ETL (Extract, Transform, Load) processing automation, and experience with both on-premise SQL databases and cloud-based data warehouse solutions. In this role, you will be instrumental in designing, developing, and maintaining robust data pipelines that integrate data from diverse sources across our portfolio companies, including electronic health records (EHRs), operational systems, and financial platforms. Your work will directly support our analytical efforts, enabling data-driven decision-making to enhance patient care and operational excellence. This position is part of the Data Team in Information Technology (IT) department and reports to the Director of Data Platforms and Reporting.

 

Duties and Responsibilities: 

The Data Engineer's responsibilities are structured across four critical domains: Architecture, Development, Operations, and Security.

 

Architecture:

• Design, develop, and maintain scalable and efficient ETL pipelines for transferring data between various source systems and our data warehouses.
• Identify and implement opportunities for process improvement and automation within the data engineering function, shaping the future state of our data platform.
• Develop and maintain comprehensive documentation for all data pipelines, processes, and data models.
• Stay up-to-date with the latest trends and technologies in data engineering, cloud platforms, and data warehousing to inform strategic architectural decisions.

Development:

• Automate data ingestion, transformation, and loading processes using a variety of tools and technologies.
• Work extensively with native server-based SQL database servers (e.g., SQL Server, PostgreSQL, MySQL) for data extraction and manipulation.
• Integrate data from and to cloud-based data warehouse solutions, including:
  • Salesforce Data Cloud: Develop and optimize data flows between Salesforce and our centralized data repositories.
  • Google BigQuery: Design and implement data loading and transformation processes within BigQuery for large-scale analytical datasets.
  • MuleSoft: Utilize MuleSoft Anypoint Platform for API-led connectivity and integration with various data sources and targets.

• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and translate them into technical solutions.

Operations:

• Monitor and troubleshoot data pipeline performance, ensuring data accuracy, completeness, and timely delivery.
• Implement data quality checks and validation processes to ensure data integrity before and after transformation.
• Manage job scheduling, dependencies, and performance tuning of all operational data flows.