Senior Data Engineer, Core Data Platform
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Job Description
Senior Data Engineer designing, implementing, and optimizing data solutions at 1upHealth, improving patient experience through better data accessibility and analytics.
Responsibilities:
- Design, develop, and implement robust ETL/ELT data pipelines for large-scale data ingestion, transformation, and storage.
- Ensure data quality, integrity, and governance by implementing validation techniques, data monitoring, and automated testing.
- Collaborate with cross-functional teams, including data scientists, analysts, platform engineers, and business stakeholders, to develop scalable and reusable data solutions.
- Automate deployments and testing using CI/CD pipelines with Git, Terraform, GitHub Actions, or Jenkins.
- Design and build custom data tools and abstractions to support analytics, machine learning, and real-time data processing.
- Work with DevOps and platform teams to establish efficient deployment and monitoring processes for internal and external data products.
- Develop and implement alerting, monitoring, and observability frameworks for data pipelines to ensure reliability and proactive issue resolution.
- Contribute to the data architecture and strategy, driving improvements in scalability, performance, and cost optimization.
- Stay up to date with emerging technologies and industry best practices to continuously enhance data engineering capabilities.
Requirements:
- 5+ years of hands-on experience in data engineering, with expertise in distributed data processing and big data frameworks (e.g., Apache Spark, Apache Iceberg, Trino, Apache Airflow, dbt, Dagster).
- Advanced programming skills in Scala or Python for data transformation and automation.
- Experience with real-time data streaming technologies such as Apache Flink, Spark Streaming, or Kafka.
- Strong experience in performance tuning for Spark and optimizing large-scale data workflows.
- Proficiency in SQL and database management, with hands-on experience in Massively Parallel Processing (MPP) databases such as Amazon Redshift, Snowflake, Teradata.
- Familiarity with cloud-based data services (AWS, RDS, DynamoDB) and containerized infrastructure (EKS, Docker, Kubernetes).
- Hands-on experience integrating DevOps and CI/CD practices in data engineering using GitHub Actions, Jenkins, or Terraform.
- Proven ability to build monitoring, alerting, and observability tools for data pipelines to ensure high availability and reliability.
- Experience in data mapping, validation, and testing frameworks to ensure accuracy and consistency.
- Exposure in machine learning/deep learning using PyTorch, Tensorflow, or Keras (PyTorch preferred)
- Exposure to machine learning workflows and familiarity with MLOps tools for model deployment and lifecycle management.
- Self-starter with strong problem-solving skills who thrives in a fast-paced, agile environment.
Benefits:
- 100% Paid BCBS Medical and Dental Insurance for Employees
- Vision Insurance
- Flexible PTO
- Equity for All Employees
- 401(k)
- Home Office Stipend
- Lifestyle Savings Account
- Parental Leave (6 weeks bonding leave for all new parents + 10 weeks for birthing parents)
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