Principal Data Engineer

New

Remote USFull-TimeSenior

SalaryCompensation for this role is based on experience, skills, and location, and includes base salary plus eligibility for performance bonuses and equity grants.

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Job Details

Experience: 7+ years
Required Skills: AWSPythonSQLKafkaSnowflakedbtDatabricksPySpark

Requirements

7+ years of hands-on experience designing and operating large-scale, distributed data systems in cloud environments.
Expert-level proficiency in Python, SQL, and PySpark.
Proven experience building production-grade ETL/ELT pipelines using Databricks or Airflow.
Strong working knowledge of AWS-based data services like S3, SQS, Lambda, and IAM.
Experience working with dbt, Delta Lake, or Kafka in event-driven architectures.
Hands-on experience with Snowflake or other cloud data warehouses including schema design.
Demonstrated ability to design scalable, resilient systems requiring knowledge of distributed computing.
Working experience with healthcare data domains such as claims, eligibility, provider, or clinical datasets.
Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related field.

Responsibilities

Architect enterprise-scale data solutions using PySpark, SparkSQL, Databricks Workflows, and distributed processing.
Develop end-to-end ingestion and transformation frameworks integrating Databricks, Snowflake, and AWS services.
Serve as the technical lead for complex client implementations defining highly available and fault-tolerant architectures.
Establish and champion best practices for CI/CD, code quality, testing, monitoring, and observability.
Design security-first data solutions ensuring alignment with HIPAA and SOC 2 requirements.
Profile and tune compute workloads, cluster configurations, and caching strategies.
Mentor senior and junior engineers while conducting design and code reviews.

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