Data Engineer II

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

📋 Description

• Design, develop, and sustain scalable ETL/ELT data pipelines for handling high-volume healthcare data.

• Write, enhance, and oversee complex SQL queries for data transformation, validation, and performance optimization.

• Create and manage Apache Airflow workflows, which include DAG creation, monitoring, and troubleshooting.

• Improve and expand the capabilities of the data platform for analytics, product features, and AI/ML applications.

• Construct and uphold data quality frameworks that incorporate automated profiling, validation, and testing.

• Oversee and optimize pipeline performance, reliability, and efficiency in a production environment.

• Investigate intricate data issues, determine root causes, and execute scalable solutions.

• Present findings to both technical and non-technical stakeholders.

• Work collaboratively with Data Operations, Product, Analytics, and Data Science teams.

• Collaborate with clinical and analytics teams to implement data-driven insights and reporting solutions.

• Document data pipelines, data models, and engineering processes.

⛳️ Requirements

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

• A minimum of 3 years of professional experience in data engineering or a related area.

• Strong command of SQL, encompassing complex querying, data transformation, and performance tuning.

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

• Experience in designing and constructing data pipelines (ETL/ELT).

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

• Familiarity with workflow orchestration tools, specifically Apache Airflow.

• Experience utilizing dbt to develop, test, and manage modular data transformation workflows.

• Knowledge of cloud platforms, particularly AWS, including S3, RDS, Lambda, Glue, and DMS.

• Proficient with version control systems and collaborative development workflows, such as GitHub or Bitbucket.

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

• Experience in supporting data quality initiatives.

• Familiarity with data modeling and data warehousing concepts, such as dimensional modeling.

• Strong analytical and problem-solving capabilities.

• Excellent written and verbal communication skills.

• Ability to collaborate successfully in cross-functional settings.

• Meticulous attention to detail and a commitment to data accuracy, consistency, and quality.

• Capacity to manage multiple priorities and deliver high-caliber work in a dynamic environment.

• Ability to stand and sit for prolonged periods.

• Capability to lift weights of up to 50 lbs.

🏝️ Benefits

• No benefits, perks, or compensation extras are specified in the posting.