Data Engineer - Mid Level

USAA•Charlotte, NC

14h

About The Position

As a mid-level Data Engineer at USAA, you will work across all phases of the data management lifecycle, including gathering and analyzing requirements and collecting, processing, storing, securing, and archiving data. You will develop and maintain technical systems for data reporting and technical solutions using emerging technologies, partnering with the business to ensure data management solutions align with business objectives. You will independently conduct the full life cycle of data engineering work, including analysis, solution design, data pipeline engineering, testing, deployment, scheduling, and production support. The role also involves designing and implementing complex solutions for data engineering and analytic systems, addressing technical problems and architecture deficiencies, collaborating on design reviews, and influencing technical adoption. You will work with engineers on complex assignments, help onboard entry-level engineers, and may begin mentoring junior engineers. The position acquires data from multiple sources and maintains databases, data warehouses, and/or data lakes. It also supports the development and enforcement of data development tools and standards, regular code reviews, and effective identification and management of risks in accordance with risk and compliance policies. USAA does not provide visa sponsorship for this role. Applications are accepted on an ongoing basis until the position is filled.

Requirements

Bachelor's degree, or four years of relevant education and/or experience.
Four years of data engineering, data analysis, or software development experience implementing data solutions, including at least one year of data engineering or data management experience.
Extensive knowledge and working experience in SQL and relational databases.
Understanding of Agile methodology.
Strong analytical and problem-solving skills.
Proficiency working with cloud technologies and tools.

Nice To Haves

Snowflake
dbt
Kafka
APIs
Python
Data modeling
Fivetran
Git/version control

Responsibilities

Conduct the full data engineering lifecycle, including analysis, solution design, data pipeline engineering, testing, deployment, scheduling, and production support.
Design and implement complex technical solutions for data engineering and analytic systems.
Identify and solve significant technical problems and architecture deficiencies, including design, security, and performance issues.
Contribute feedback and recommendations during design reviews.
Break down business features into technical stories and approaches.
Influence stakeholders in adopting the best technical solutions.
Create proofs of concept and prototypes to advance complex initiatives.
Collaborate with the team and other engineers on new technologies and alternatives to plan and execute complex assignments.
Help onboard entry-level engineers and potentially mentor junior engineers.
Acquire data from multiple data sources and maintain resulting databases, data warehouses, and/or data lakes.
Help develop, maintain, and enforce company data development tools and standards.
Conduct regular code reviews to improve quality and ensure compliance.
Ensure risks associated with business activities are identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.