Data EngineerPlatinum Resource Group • Carlsbad, CA
Data Engineer
Platinum Resource Group • Carlsbad, CA
[job_card.30_days_ago]
[job_preview.job_type]
- [job_card.full_time]
[job_card.job_description]years of experience in data engineering, data architecture, or advanced analytics environments. Strong experience building and managing pipelines with Databricks, Spark, or similar distributed data processing platforms. Proficiency in Python, SQL, and cloud data technologies (Azure, AWS, or GCP). Solid understanding of ETL / ELT design, data modeling, and data warehousing principles. Experience working within or supporting AI / ML environments strongly preferred. Strong analytical and problem-solving skills, with an ability to translate business needs into scalable technical solutions. Excellent communication skills and a collaborative mindset for cross-functional work with data science and business teams. Bachelor's degree in Computer Science, Engineering, or related field; Master's degree a plus. Candidates must be authorized to work in the United States without sponsorship.
JOB DESCRIPTION
The Data Engineer will play a key role in advancing the company's AI-driven data strategy. The organization has made significant investments in Databricks and is building an AI-forward environment to unlock next-generation analytics and automation. Working under the Director of Data Engineering and partnering with the VP of Data and Analytics, this individual will help leverage Databricks and related cloud technologies to modernize data architecture, enable scalable AI initiatives, and deliver trusted data for business decision-making.
- Design, build, and optimize scalable data pipelines and architectures to support AI, machine learning, and enterprise analytics.
- Collaborate closely with data scientists, analysts, and business stakeholders to ensure data availability, integrity, and readiness for AI use cases.
- Implement modern data engineering practices using Databricks, Spark, and cloud-native services (Azure, AWS, or GCP).
- Contribute to modernization of the company's data infrastructure to improve efficiency, automation, and scalability.
- Develop and maintain ETL / ELT processes, data models, and integration frameworks supporting analytical and operational workloads.
- Champion data governance, quality, and security best practices across the organization.
- Support deployment and integration of AI / ML models into production pipelines.
- Monitor and tune system performance, identify bottlenecks, and implement process improvements.
- Document architecture, workflows, and data lineage for transparency and reusability.
QUALIFICATIONS
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