Data Engineer

Location:

Senior Data Engineer

The Data Engineer will help expand and optimize our data and data pipeline architecture, as well as optimize data flow and collection for cross-functional teams.

The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.

The Data Engineer will support Software Developers, Data Quality Engineers, Data Analysts, and Data Scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.

Responsibilities

• Create and maintain optimal data pipeline architecture.
  
• Assemble complex data sets that meet functional/non-functional requirements.
  
• Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
  
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, dbt, and AWS big data technologies.
  
• Build analytics tools that utilize the data pipeline to provide actionable insights into employee experience, operational efficiency, and other key business performance metrics.
  
• Work with stakeholders to assist with data-related technical issues and support associated data infrastructure needs.
  
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
  
• Stay up to date with the latest features and capabilities from public cloud providers (AWS, Azure) and apply them to enhance the team.
  
• Collaborate with data scientists and analysts to strive for greater functionality in our data systems.
  

Minimum Qualifications

• 5+ years of experience as a Data Engineer.
  
• Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field.
  
• 5+ years of hands-on experience with

  Snowflake

  .
• 5+ years of experience with

  dbt

  , including advanced dbt concepts like macros and Jinja templating.
• Advanced working SQL experience with relational databases and query authoring.
  
• Experience with scripting languages such as

  Python

  .
• Experience with big data tools such as

  PySpark

  .
• Experience with

  AWS cloud services

  commonly used for data engineering, including S3, EC2, Glue, Lambda, RDS, or Redshift.
• Experience working with APIs to pull and push data.
  
• Experience optimizing big data pipelines, architectures, and data sets.
  
• Experience performing root cause analysis on data and processes to answer business questions and identify improvement opportunities.
  

Preferred Qualifications

• Experience with

  AWS CloudFormation

  templates is a plus.
• Familiarity with

  Agile and SCRUM

  methodologies is a plus.
• Experience developing dashboards with

  PowerBI

  is a plus.
• Analytical skills for working with unstructured datasets.
  
• Proven history of extracting value from large, disconnected datasets.
  
• Experience working with agile, globally distributed teams.