Senior Data Infrastructure Engineer

October 17

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Libertas Funding, LLC

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Description

• Be the “go-to person” for all things related to data engineering. • Libertas Data Engineer primarily supports the business intelligence and data science teams at the Company. • All data infrastructure builds must be able to scale and extend to other areas of Libertas’ technology and software development. • Weigh pros and cons of automating vs. introducing customizations to the Company’s data infrastructure. • Scope, design, and implement repeatable automation of the data, build, test, deploy and release processes. • Automate timely and accurate delivery of reporting and analytics data. • Build and maintain robust, observable (ETL) data pipelines. • Update and maintain AWS cloud and on-premises data warehouse configuration and components. • Investigate and remediate technical issues. • Create and maintain documentation as it relates to system configuration, mapping, processes, and service records. • Build and maintain continuous integration and continuous delivery (CI/CD) technologies. • Provide technical expertise at building and managing infrastructure as code (IaC). • Maintain performance and SLA metrics for build/release systems. • Collaborate within the development team to enable the team to meet goals and objectives. • Proactively document and communicate knowledge to enable others to quickly solve the next challenge. • Adhere to compliance procedures and internal/operational risk controls in accordance with all applicable regulatory standards, requirements, and policies.

Requirements

• 7+ years of software engineering (4+ as data engineer) experience designing, developing, and delivering application solutions for enterprise-level development and integration projects. • Strong communication skills and previous experience working with cross-functional business groups. • Experience with maintaining, updating, and integrating data pipelines and data warehouses. • Proficiency in capture and maintenance of data in SQL and NoSQL databases. • Proficiency in fast-paced software engineering team, following software engineering development cycles. • Strong sense of agency and self-initiative / intrinsic motivation to push projects forward, learn new tech & tools. • Process-oriented, detail-oriented, and analytically oriented mindset • Natural enjoyment from solving complex problems with a methodical approach. • Strong analytical and problem-solving skills with a focus on solving business problems. • Experience working in Agile software development processes. • Deep knowledge of Continuous Integration and Delivery and how to build deployment pipelines and infrastructure that empowers development teams. • Experience with CloudWatch, IAM, Lamdba • Terraform, Cloud Formation, Puppet, or other Infrastructure as Code (IaC) technologies. • Proficiency in Git, Git Actions, and Git workflows. • Experience with logging and monitoring tools. • Knowledge of data governance best practices, including data quality/integrity and privacy.