Hire Direct


Job Description:

Responsibilities of the Analytics Engineer:
  • Integration of data from multiple data sources
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Hands on development of Tableau dashboards using multiple data sources
  • Create and maintain optimal data pipeline architecture especially around accounting and financial systems
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Conceptualize and design the best fit solution against desired requirements for data delivery
  • Work with stakeholders including the Managers, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  • Work with data and analytics experts to strive for greater functionality in our data systems.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Skills and Experience of the Analytics Engineer:
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • 2+ years of experience in Business Intelligence and Data Visualization tools and techniques with Tableau
  • 2+ years of experience in an analytics Engineer role
  • Experience with relational SQL databases, including SQL server and Postgres.
  • Experience with AWS cloud services: EC2, EMR, RDS, Redshift
  • Experience with Tableau or comparable experience with other BI visualization tool such as QlikView or Domo
  • Experience with any object-oriented/object function scripting languages: C#, Python, Java, C++, Scala, etc.
  • Preferred experience with big data tools: Hadoop, Spark, Kafka, etc.
  • Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets.
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.


Snowflake, Tableau, Python, SQL