Key Responsibilities: Design and develop robust data schemas and comprehensive data models by collaborating with data teams to analyze, structure, and integrate large, complex datasets from diverse sources Architect and implement scalable Data Warehouse and Data Lake Solutions using modern tools like BigQuery, Snowflake, and Google Cloud SQL, ensuring alignment with healthcare standards Design, optimize, and maintain scalable ETL/ELT pipelines to efficiently ingest, clean, transform, and integrate diverse healthcare data from multiple sources into a centralized data warehouse or data lake, ensuring seamless data flow and accessibility Leverage the full suite of Google Cloud Platform (GCP) toolsincluding BigQuery, Dataflow, Cloud Storage, Cloud Composer, and Cloud SQLto design, implement, and optimize scalable, efficient end-to-end ETL/ELT pipelines and data processing workflows for healthcare data. Analyze, design, code, and test complex ETL processes for data warehouses and operational data stores Write and optimize Python and SQL scripts for data processing, ensuring high performance and cost-efficiency. Develop and maintain robust, HIPAA-compliant data systems and process frameworks to seamlessly integrate sensitive healthcare data from diverse sources such as EHRs, public datasets, and APIs Implement automated data collection, transformation, and storage processes to enhance data accessibility and quality Continuously monitor and optimize data workflows for performance and cost-effectivenessData Governance & Data Quality Assurance Collaborate on establishing and maintaining a robust data governance framework that ensures compliance with healthcare regulations, including HIPAA, while promoting data integrity and security. Collaborate in the development and implementation of data quality management strategies, utilizing tools like data catalogs, lineage tracking, and business glossaries to ensure accuracy, consistency, and transparency across data assets. Drive initiatives for data integrity, consistency, and security across all platforms and systems Maintain documentation of data architectures, pipelines, and processes.Collaboration and Stakeholder Engagement Collaborate with cross-functional teams to understand data needs and implement effective solutions. Partner with internal and external stakeholders, including senior leadership, to align data engineering initiatives with organizational goals. Work closely with third-party vendors and consultants to ensure the delivery of high-quality solutions. Actively participate in strategic planning, providing insights and recommendations for data-driven decision-making. Performs other duties and projects as assigned. Qualifications: Bachelors degree in computer science, Engineering, Information Systems, or a related field required; Masters preferred. Must have at least 4-8 years in data engineering and data ops, preferably within healthcare data environments. Expertise in designing scalable data architectures, with hands-on experience in data warehousing, modeling, ETL/ELT processes, and integrating large datasets from diverse sources, while building and maintaining robust data pipelines using modern data engineering tools and frameworks. Proficient in designing and implementing data architectures on Google Cloud Platform (GCP), with hands-on experience leveraging a range of services including BigQuery, Dataflow, Pub/Sub, Cloud Composer (Airflow), Cloud Storage, BigTable, Data Fusion, Dataproc, Cloud Functions, Cloud Run and Cloud Spanner Preferred industry-recognized certifications, such as Google Cloud Certified Professional Data Engineer, or equivalent credentials in Google Cloud Platform (GCP), data engineering, or related technologies Proficiency in Apache Kafka or Cloud Pub/Sub to design and implement real-time data processing systems that efficiently handle and stream data feeds. Proficiency in Python, SQL, and experience with ETL/ELT frameworks Strong expertise in SQL databases with the ability to efficiently execute complex queries and optimize database performance. Create automated data quality monitoring and alerting systems Strong grasp of data governance, quality assurance, and compliance standards. Familiarity with data visualization and business intelligence tools, including Tableau and/or Power BI Understanding of AI/ML pipelines and MLOps, is a plus Understanding of healthcare data standards (e.g., HL7, FHIR, ICD-10) and systems (e.g., EHRs). Knowledgeable in current data security practices and compliance standards relevant to healthcare, such as HIPAA.Employee Benefits:We offer a comprehensive compensation and benefits package designed to attract and retain top talent. Here's what you can expect:Competitive salary commensurate with your experience and qualifications.Access to health, dental, and vision insurance plans, with the company covering half of the premium costs.Access to 401(k)-retirement plan to help you secure your financial future.Enjoy 22 paid holidays throughout the year.Receive an educational stipend to support your ongoing professional development.A technology allowance to keep you equipped with the tools you need.Generous paid time off to recharge and maintain work-life balance.Acclinate Inc. is an equal opportunity employer and prohibits discrimination based on race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws. recblid lursyvwsgeonzhx02ekk4rziirqvhy