Data Engineer II - AI Products
US-CO-Denver
Attract-careers1
Req #: 93906
Type: Fulltime-Regular
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Overview: Our Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our team members play a vital role in connecting consumers with the products and platforms of tomorrow. Responsibilities: Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session. Key Responsibilities: * Design, implement, and optimize scalable, secure data pipelines using Databricks, Spark, and Delta Lake. * Build robust ingestion, transformation, and CI/CD workflows with GitLab, ensuring performance, reliability, and cost-efficiency. * Apply software engineering best practices (SOLID, modular design, version control) to data workflows. * Develop unit tests, reusable testing frameworks, and enforce code quality through reviews and mentorship. * Refactor and maintain existing codebases for scalability, stability, and performance. * Collaborate with cross-functional teams and contribute to Agile ceremonies, shared libraries, documentation, and infrastructure standards. Qualifications: Education and Experience: * Bachelor's degree in Computer Science, Information Systems, or related field (Master's preferred). * 2-4+ years of data engineering experience building large-scale pipelines with Python, Databricks, Spark, and Delta Lake. * Proven ability to apply SOLID principles, design patterns, and best practices to data solutions. * Experience with ML/NLP frameworks and infrastructure-as-code tools (Terraform, CDK, CloudFormation) a plus. Skills and Qualifications: * Proficient in Python (required) and Scala, with experience writing clean, testable, and modular code. * Strong understanding of data engineering principles, distributed systems, and modern data architecture. * Skilled in CI/CD practices, DevOps workflows, and automation of data pipeline deployments. * Experienced with unit testing (e.g., pytest) and ensuring data quality and pipeline reliability. * Familiar with AWS, containerization (Docker), and orchestration tools (ECS, EKS, Kubernetes). * Strong communication, problem-solving, and collaboration skills; prior experience handling sensitive data is a plus. Visa sponsorship not available for this role
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