DaTa Engineer

Company Description

Jobrion is a career-focused organization that streamlines the job application process for professionals across industries. The company identifies relevant opportunities, optimizes resumes for applicant tracking systems (ATS), and enhances candidate visibility with employers. By handling time-consuming application tasks, Jobrion enables professionals to concentrate on interview preparation and skill development. Team members contribute to building data-driven solutions that improve how job seekers connect with roles that match their experience and goals.

Role Description

The Data Engineer will design, build, and maintain scalable data pipelines and infrastructure that support Jobrion’s analytics, recommendation, and automation capabilities. This full-time, on-site role is based in the Austin, Texas Metropolitan Area and involves collaborating with product, analytics, and engineering teams to understand data requirements and translate them into robust technical solutions. Day-to-day responsibilities include developing and optimizing ETL processes, modeling and warehousing data from multiple internal and external sources, and ensuring data quality, reliability, and security across systems. The role also includes monitoring data workflows, troubleshooting performance issues, documenting data architecture, and contributing to continuous improvements in how Jobrion manages and uses data.

Qualifications

• Strong data engineering skills, including experience with scalable data pipelines, distributed processing frameworks, and data integration tools.

• Proficiency in data modeling and data warehousing, with the ability to design efficient schemas and support reporting and analytics use cases.

• Hands-on experience with Extract Transform Load (ETL) development, workflow orchestration, and automation of data ingestion from multiple sources.

• Applied data analytics skills, including querying large datasets, building data sets for analysis, and collaborating with analytics or BI teams.

• Proficiency in SQL and at least one programming language commonly used in data engineering (e.g., Python, Java, or Scala).

• Experience with cloud data platforms (e.g., AWS, Azure, or GCP) and modern data stack tools (e.g., Spark, Airflow, dbt, or similar) is highly beneficial.

• Familiarity with data governance, security, and best practices for handling sensitive information, including logging, monitoring, and documentation.

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.

• Ability to work collaboratively on-site, communicate clearly with cross-functional teams, and manage multiple priorities in a dynamic environment.