ringDNA, the company that uses AI to help every rep sell like an expert, is led by an award-winning executive leadership team and backed by Goldman Sachs, Bryant Stibel and Palisades Growth Capital. ringDNA was named one of the "Best Places to Work" by BuiltinLA and Comparably. The company was named one of the best privately owned companies in America by Entrepreneur and has been in the JMP Hot 100 for three years running. 

ringDNA offers talented candidates a chance to work with executive mentors in a rapid growth environment where teammates are passionate about our transformative technology, vibrant culture and collaborative mindset. See why people love working at ringDNA.

Who We’re Looking For

We are searching for a Data Engineer who is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. 

How We’ll Support You

You’ll have lots of resources at your disposal, including our Data Engineering team to support our software developers, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.

Duties in Detail

• Create and maintain optimal data pipeline architecture to deliver reports to end-users and data scientists.
• Assemble large, complex data sets that meet business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a variety of data sources using SQL and AWS technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Engineering, Data Science, 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.

Candidate Requirements

• Advanced SQL knowledge.
• 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.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 3-5 years of experience in a Data Engineer role, who has attained an undergraduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
  
  • MySQL, Postgres and Redis
  • RDS, Redshift, Glue
  • Python (required), Java, C++, or Scala (nice to have)
  • Airflow, Kinesis, Kafka (nice to have)