Data Engineer II

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and maintain scalable data pipelines (ETL/ELT) to facilitate the ingestion, transformation, and delivery of substantial healthcare data.

• Write, optimize, and sustain intricate SQL queries for data transformation, validation, and performance enhancement.

• Develop and oversee workflow orchestration utilizing Apache Airflow, encompassing DAG creation, monitoring, and troubleshooting.

• Augment and expand data platform capabilities to accommodate analytics, product features, and AI/ML applications.

• Construct and uphold data quality frameworks, including automated data profiling, validation, and testing procedures.

• Monitor and enhance pipeline performance, reliability, and efficiency within production environments.

• Analyze complex data challenges, determine root causes, and implement scalable solutions, effectively communicating findings to both technical and non-technical audiences.

• Collaborate with cross-functional teams (Data Operations, Product, Analytics, Data Science) to gather requirements and provide high-quality data solutions.

• Partner with clinical and analytics teams to operationalize data-driven insights and reporting solutions.

• Contribute to the documentation of data pipelines, data models, and engineering processes to promote maintainability and knowledge sharing.

⛳️ Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience.

• 3+ years of professional experience in data engineering or a related domain.

• Strong expertise in SQL, including complex querying, data transformation, and performance optimization.

• Proficient in Python for data processing, automation, and integration tasks.

• Experience in designing and constructing data pipelines (ETL/ELT) to facilitate data ingestion, transformation, and delivery.

• Practical experience with contemporary data warehousing platforms, such as Snowflake, PostgreSQL, Amazon Redshift, or Microsoft SQL Server.

• Familiarity with workflow orchestration tools, especially Apache Airflow (DAG development, debugging, and maintenance).

• Experience utilizing dbt (data build tool) to develop, test, and manage modular data transformation workflows.

• Experience working with cloud platforms, particularly AWS (e.g., S3, RDS, Lambda, Glue, DMS).

• Familiarity with version control systems and collaborative development processes, such as GitHub or Bitbucket.

• Understanding of CI/CD practices and tools, including Jenkins or GitHub Actions.

• Experience supporting data quality initiatives, encompassing data profiling, validation, or monitoring frameworks.

• Knowledge of data modeling and data warehousing concepts, including dimensional modeling.

• Exposure to analytics, reporting, or data visualization tools (e.g., Tableau, Looker) is advantageous.

• Experience with healthcare data, including claims or clinical datasets, is beneficial.

• Familiarity with data science or machine learning workflows from a data engineering viewpoint is a plus.

🏝️ Benefits

• 100% Company-Paid Employee Coverage - Medical, dental, and vision plans with a 100% company-paid employee-only option, plus company contributions toward dependent coverage and company-paid life and disability insurance.

• 401(k) + 4% Match

• 6 Weeks Parental Leave

• Invest in You - 30-60-90 day plans and frequent training

• Culture of Recognition - peer-to-peer bonuses & team celebrations