Senior Data Engineer

Ascent•San Diego, CA

13d•$125,000 - $135,000

About The Position

Ascent is a leading provider of innovative financial products and student support services that enable more students to access education and achieve academic and economic success. Everything Ascent offers is designed with the best-in-class teams and technology to increase every student's ability to plan, pay, and succeed in their education and career. Ascent's planning tools and financing resources are co-created by students for those in college, graduate school, and career training programs. Ascent offers financial wellness education, student success services, and one-on-one and digital career coaching that put students' academic and professional goals within reach. Ascent has been widely recognized for its strong culture – named “Best Places to Work” by the San Diego Business Journal for the past 5 years – and as an industry leader – named “Best Student Loan” by NerdWallet for the past 3 years. This job description outlines the objective, primary responsibilties, requirements and qualifications of the Senior Data Engineer.

Requirements

Bachelor’s Degree required in Computer Science, Engineering, Statistics, Applied Mathematics, Informatics, Information Systems, or another quantitative field.
5+ years of experience in a data engineering role.
Enjoy working in cross-functional teams and providing feedback to senior management.
Exceptional analytic and strategic thinking skills related to working with structured and unstructured data sets.
Experience and proficiency with…
Advanced SQL and procedural practices.
Building and optimizing data pipelines, architectures, and data sets.
Performing root cause analysis on internal/external data, identifying improvement opportunities.
Relational databases (MS SQL Server, Postgres, MySQL) and NoSQL databases.
AWS cloud services (EC2, EMR, RDS, Redshift) and AWS Data Pipeline.
Big data pipeline tools like Spark, Glue and SSIS
Sourcing and modeling data from REST APIs.
Data visualization systems like Tableau, Looker or Power BI.
Object-oriented scripting languages (Python, Scala).
Experience with DBT and Airbyte(Or similar ETL tool).
Strong dimensional modeling capabilities.
Development operations in the data engineering space (git, ci/cd pipelines).
Must be able to think outside of the box, enjoy being challenged to grow your skills, and not be afraid to step outside of your comfort zone.

Nice To Haves

Past consumer finance experience and / or experience in a highly regulated environment.
Experience in Dagster and Kubernetes
MBA or Master’s degree in Computer Science, Engineering, Statistics, Applied Mathematics, Informatics, Information Systems or another quantitative field.

Responsibilities

Work with stakeholders including Executive, Product, Data and Marketing teams to assist with data-related technical issues and support their data infrastructure needs.
Assemble large, complex data sets that meet functional / non-functional business requirements.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python and AWS ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Be proactive to identify systems and processes the improve efficiencies and support greater access to meaningful data that empowers key stakeholders throughout the organization.
Find ways to ensure clean data and reduce risk of fraud.
Optimize performance in Amazon Redshift
Design Scala data architecture Pipelines.