Senior Software Engineer, Data Engineering
New
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Omada HealthDigital Healthcare
Remote, USAFull-TimeSenior
SalaryCalifornia, New York State and Washington State Base Compensation Ranges: $179,400 - $224,300*, Colorado Base Compensation Ranges: $171,600 - $214,500*. Other states may vary.
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Job Details
- Experience
- 5+ years of experience building, maintaining, and orchestrating scalable data pipelines. 3+ years of experience as a data engineer developing or maintaining integration with software such as Airflow or any Python-based data pipeline codebase.
- Required Skills
- AWSPostgreSQLPythonSQLETLJavaAirflowScalaData modelingRedshift
Requirements
- 5+ years of experience building, maintaining, and orchestrating scalable data pipelines.
- 3+ years of experience as a data engineer developing or maintaining integration with Airflow or any Python-based data pipeline codebase.
- Proficiency in SQL and relational databases (MySQL, PostgreSQL).
- Proficiency in Analytical SQL and massive parallel processing (MPP) databases (Redshift, BigQuery, Snowflake).
- Proficiency in Python, Java, or Scala.
- Experience with cloud platforms such as Amazon AWS.
- Experience in backend software development for distributed computing.
- Experience in data modeling for OLTP and OLAP applications.
- Experience working with sensitive data (PHI/PII) and security best practices.
- Knowledge of data governance practices and principles.
- Bachelor’s degree in Computer Science or a similar discipline preferred.
Responsibilities
- Design, develop, and implement scalable, secure, and efficient data solutions.
- Create and maintain logical and physical data models to support analytics and reporting.
- Build and optimize ETL processes and data pipelines to ensure efficient data flow.
- Integrate diverse data sources including APIs, databases, and third-party data.
- Monitor and optimize data system performance to ensure low latency and high throughput.
- Implement data quality checks, validation, and governance frameworks.
- Partner with data scientists and analysts to deliver data-driven solutions.
- Maintain comprehensive documentation for architectures, models, and pipelines.
- Train teammates in data engineering best practices.
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