Remote Senior Data Engineer

Summary

Join the Dwolla team as a Senior Data Engineer and lead efforts to leverage data to its maximum value, developing and executing technical vision for cutting-edge AWS-based data pipelines.

Requirements

• Typically requires 5+ years of experience in a closely-related role
• Experience working with infrastructure-as-code and CI/CD systems (such as Terraform, Troposphere, Cloudformation, Jenkins)
• Experience with infrastrastructure-as-code (i.e., Terraform, CloudFormation) methodologies
• Experience with distributed computing technologies such as Spark
• Experience designing and reviewing multi-function Python programs in accordance with style and security guidelines
• Experience optimizing SQL queries for high performance
• Experience with AWS database solutions such as RDS, DynamoDB and Redshift

Responsibilities

• Design, build, monitor, and maintain infrastructure-as-code AWS-based data pipelines and warehousing tooling to support both internal and client-facing use cases
• Write and optimize Python code for ETL and other jobs to populate the Dwolla Data Lake and integrate with Salesforce (and related tools)
• Help define and implement the principles and technologies for a Data Lifecycle to enable application of CI/CD principles to data problems while ensuring integrity, security, privacy, and performance
• Support the Technology department’s use of a combination of AWS database technologies through advising on implementations, troubleshooting, and maintenance
• Partner with other engineers and data specialists in writing and optimizing queries or developing performant schemas with consideration for security and privacy
• Assist other Engineers in supporting highly-available RDS database instances including user management, configuration, migrations, and performance troubleshooting
• Contribute to plans and exercises to ensure databases and data pipelines are resilient to outages and recoverable in the event of a disaster
• Communicate technical decisions through RFCs, design docs, technical training, and the wiki
• Mentor other engineers via pairing, design review, and code review

Preferred Qualifications

• Experience implementing relevant AWS technologies for the purposes of building data pipelines and executing extract, transform, load (ETL) jobs
• A knack for seeking empirical evidence through proofs of concept, tests and external research
• Empathy with the user of the work you are producing to guide decision-making

Benefits

• Unlimited Paid Time Off (with a mandatory PTO minimum of 5 days every 4 months)
• 12 weeks paid parental leave
• Medical, dental and vision insurance (Health plan options include FSA & HSA options and more…)
• Stock options
• 401k (with 4% company match)
• Long-term disability insurance
• Life insurance