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Data Engineer

2 months ago

San Francisco, California, United States GoodRx Full time
About the Role

GoodRx is seeking a highly skilled Data Engineer to join our team. As a Data Engineer, you will play a critical role in building and maintaining our cloud-based data pipelines, ensuring the accuracy and reliability of our data.

Responsibilities
  • Collaborate with cross-functional teams to design and implement data pipelines, ensuring data quality and integrity.
  • Develop and maintain ETL processes, data marts, and data warehouses to support business decisions.
  • Lead small to medium-sized projects, solving complex data problems through documentation, design, and creation of data pipelines.
  • Work closely with data scientists and analysts to ensure data is accurate, complete, and meets business requirements.
  • Develop and implement data processing pipelines using cloud technology such as AWS, Kubernetes, Airflow, Redshift, Databricks, EMR.
  • Define and manage overall schedule and availability for a variety of data sets.
  • Work closely with other engineers to enhance infrastructure, improve reliability, and efficiency.
  • Make smart engineering and product decisions based on data analysis and collaboration.
  • Act as an in-house data expert, making recommendations regarding standards for code quality and timeliness.
  • Architect cloud-based data pipeline solutions to meet stakeholder needs.
Requirements
  • Bachelor's degree in analytics, engineering, math, computer science, information technology, or related discipline.
  • 8+ years of professional experience in the big data space.
  • 8+ years of experience in engineering data pipelines using big data technologies (Spark, Flink, etc.) on large-scale data sets.
  • Expert knowledge in writing complex pySpark, SQL, dbt, and ETL development with experience processing extremely large datasets.
  • Expert in applying SCD types on S3 data lake using Databricks/Delta Lake.
  • Experience with data model principles and data cataloging.
  • Experience with job scheduler Airflow or similar.
  • Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions.
  • Deep familiarity with AWS Services (S3, Event Bridge, Kinesis, Glue, EMR, Lambda).
  • Experience with data warehouse platforms such as Redshift, Databricks, Big Query, Snowflake.
  • Ability to quickly learn complex domains and new technologies.
  • Innately curious and organized with the drive to analyze data to identify deliverables, anomalies, and gaps and propose solutions to address these findings.
  • Thrives in a fast-paced startup environment.
Good to Have
  • Experience with customer data platform tools such as Segment.
  • Experience with data streaming such as Kafka.
  • Experience using Jira, GitHub, Docker, CodeFresh, Terraform.
  • Experience contributing to full lifecycle deployments with a focus on testing and quality.
  • Experience with data quality processes, data quality checks, validations, data quality metrics definition, and measurement.
  • AWS/Kafka/Databricks or similar certifications.