The Role 

As a Senior Data Engineer, you will be responsible for developing and implementing data pipelines, focusing on efficient extraction, transformation, and loading (ETL) processes. Your role will involve creating scalable services for data tracking, translating complex requirements into detailed designs, and exploring alternatives for streamlined data processing solutions.

This role is hybrid. 

Responsibilities 

  • Develop, implement, and maintain pipelines for ETL processes to facilitate data-driven decision-making
  • Focus on ingesting, storing, processing, and analyzing large datasets efficiently
  • Create scalable web services for tracking data to support organizational goals
  • Translate technical and functional requirements into detailed designs
  • Investigate alternatives for data storage and processing to ensure optimal solutions
  • Provide On-Call after hours support on a rotating schedule with other team members
  • Mentor junior staff members through technical training and project oversight

Qualifications  

  • Proficiency in building, implementing, and maintaining data pipelines for efficient ETL processes
  • Strong scripting and automation skills to streamline data workflows
  • Familiarity with ETL tools and frameworks such as Fivetran or other similar tools
  • Experience in maintaining and optimizing data infrastructure for accurate data processing
  • Ability to automate data workflows such as data ingestion, aggregation, and ETL processing
  • Skill in preparing raw data into consumable datasets for technical and non-technical stakeholders
  • Knowledge of data engineering principles, data visualization, and data architecture
  • Fluency in designing data models to support efficient data storage
  • Understanding of data warehousing (Redshift, Snowflake), cloud computing (AWS), and data security
  • Ability to provide data accuracy, integrity, privacy, security, and compliance
  • Monitor data systems performance and implement optimization strategies
  • Help to establish best practices in new data architecture
  • Utilize data controls to maintain privacy, security, compliance, and quality
  • Strong critical thinking and problem-solving skills to address data management issues effectively

Additional Requirements 

  • Must pass any and all required background checks  
  • Must be and remain compliant with all legal or company regulations for working in the industry  
  • Must be a minimum of 21 years of age 

 

#LI-HYBRID

 

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