Senior Data Engineer

Industry: Healthtech
Remote
Company size: 51-250
Full-time
salary
Not disclosed

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Job description

A US-based company that has developed a system to help users find medical prescriptions online and pick them up at any drugstore is looking for a Senior Data Engineer. The selected candidate will serve as a thought leader and will be building the next generation of data tools and frameworks. The platform allows patients to consult with US-licensed medical professionals and avail free home delivery. The company has managed to secure funding worth more than $170 mn so far. This is a great opportunity to work with a diverse team of professionals and experience rapid career growth.

 

Job Responsibilities:

  • Develop and maintain data products and infrastructure
  • Proactively assess production DW support trends to determine and implement short and long-term solutions
  • Communicate effectively across diverse disciplines (including product engineering, infrastructure, analytics, data science, finance, marketing, customer support, etc.) 
  • Gather requirements and describe data engineering strategy and decisions
  • Set a high bar of standard while writing and reviewing clean and correct code
  • Design and build for data integrity, reliability, and performance
  • Set code standards, and perform peer code and architecture reviews

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 5+ years of relevant experience as a data engineer
  • Extensive experience with Python software development
  • Experience building and maintaining robust and scalable data integration (ETL) pipelines using SQL, EMR, Python, and Spark
  • Demonstrable experience writing complex, highly-optimized SQL queries across large data sets
  • Experience designing and maintaining columnar databases (e.g., Redshift, Snowflake)
  • In-depth knowledge of distributed data processing (Hadoop, Spark, Hive)
  • Familiarity with ETL with batch (AWS Data Pipeline, Airflow) and streaming (Kinesis)
  • Experience designing and integrating Business Intelligence tools (e.g., Looker, QuickSight)
  • Familiarity with creating scalable data models for analytics
  • Experience designing and refactoring large enterprise data warehouses and associated ETLs
  • Experience owning features from design through delivery along with ongoing support
  • Experience providing clear data engineering technical leadership, mentoring, and best practices for data management and quality within and across teams

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