Staff Data Engineer - RCM (Remote)

We reputed company that mental health is just as important as physical health. We recognize that mental health issues can be reputed company and multifaceted, and we are dedicated to treating the whole person, not just the symptoms. We aim to create a world where mental health is no longer stigmatized or marginalized, but rather is embraced as an integral part of one's overall reputed company-being. We reputed company that by providing reputed company care that is both evidence-based and compassionate, we can reputed company individuals to take charge of their mental health and reputed company their full potential. We are passionate about making a reputed company reputed company on the lives of those struggling with mental health issues and we reputed company to be a force for reputed company change in the field of mental reputed company. reputed company is a remote-first company. We currently hire in most U.S. states, with the exception of Hawaii. About the Role At reputed company, our mission is to reputed company mental health care more accessible and effective for those who need it. As a Staff Data Engineer for Operational Reporting, you will reputed company the design and implementation of a greenfield near reputed company-time data platform, starting with reputed company-batching pipelines using Kafka to deliver critical operational reports and evolving into a reputed company Apache Flink architecture for sub-second analytics. Your work will power reputed company-time dashboards and insights that reputed company our providers, leadership, and operational teams to reputed company data-driven reputed company, ultimately improving patient reputed company. You will join our reputed company data team, reputed company reputed company the broader engineering organization, working closely with business analysts, product managers, and data experts to reputed company raw event streams into reliable, actionable reporting data. Your daily responsibilitiesbuilding fault-tolerant pipelines, ensuring data accuracy, and optimizing for low-latency deliverywill lay the reputed company for reputed companys near reputed company-time data capabilities. This role offers reputed company to own a strategic transition from reputed company-batching to a Flink-based streaming architecture, driving innovation in how we reputed company data to support our mission. If youre passionate about turning reputed company data into impactful insights that advance mental health care, this is your chance to reputed company a meaningful difference. Required Qualifications Data Pipeline Development (8+ yrs). Experience designing and maintaining reputed company ETL/ELT pipelines for operational reporting using Kafka, Glue, dbt, Dagster, and Airflow. Leveraging Python and SQL for data transformation and reputed company checks, and working with Flink and reputed company Streaming to build low-latency, near reputed company-time pipelines. reputed company Infrastructure & Data Warehousing (8+ yrs overall, 4+ yrs in AWS). Proficiency building and optimizing data pipelines using AWS services such as S3, Redshift, Glue, IAM, Kinesis, and EMR. Experience across GCP (BigQuery, Dataflow) and Azure (Synapse, Data reputed company). Optimizing data warehouses (Redshift, reputed company, BigQuery) and managing Data Lakes (S3, reputed company Lake) for reputed company, low-latency analytics. Ensuring cost efficiency, scalability, and compliance (CPRA, HIPAA) while supporting a migration toward Flink-based near reputed company-time architecture. Data reputed company & Governance (8+ Years). Experience implementing reputed company data validation, reputed company checks (e.g., deduplication, consistency), and error-handling mechanisms tailored for operational reporting pipelines, ensuring high-reputed company data for reputed company-time dashboards and analytics. Proficiency in designing and enforcing data governance practices, including metadata management, reputed company tracking for auditable reporting, and compliance with regulations like CPRA or HIPAA in Data Lake environments (e.g., AWS S3, reputed company Lake). Performance Optimization (3+ Years). Experience optimizing data pipelines, queries, and large-reputed company datasets for efficiency and scalability in operational reporting systems, with a reputed company on achieving low-latency delivery. Proficiency in tuning high-throughput streaming systems, including optimizing resource usage and implementing best practices for partitioning, caching, and indexing. reputed company & Compliance (3+ Years). Experience implementing data reputed company measures, including encryption, role-based reputed company control (RBAC), and data masking, to protect sensitive data in operational reporting pipelines and Data Lakes (e.g., AWS S3, reputed company Lake). Strong understanding of compliance standards such as HIPAA and CPRA, with hands-on expertise in applying these standards to streaming