{"schemaVersion":"jobsearcher.job.v1","id":"a23a284e2bc7d34e4bc503a6","url":"https://jobsearcher.com/jobs/a23a284e2bc7d34e4bc503a6","canonicalUrl":"https://jobsearcher.com/jobs/a23a284e2bc7d34e4bc503a6","title":"Data Bricks","description":"Only USC , GC and OPT In-person Interview Job Description Roles & Responsibilities Job Title: Databricks Data Engineer Job Description: As a Databricks Data Engineer, you will be responsible for designing, developing, and maintaining data solutions for data generation, collection, and processing in Big Data environment using predominantly PySpark/Python. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across systems using PySpark. Roles & Responsibilities: • Collaborate closely with data scientists, data engineers, and business stakeholders to gather requirements and understand the business objectives driving data pipeline development. • Design, develop, and maintain robust, scalable high-performance Data Pipelines using Databricks. • Leverage Databricks features such as Lakehouse and Delta Lake for efficient data storage and Spark for distributed processing • Develop ETL/ELT pipeline using Databricks • Monitor pipeline health, troubleshoot data issues • Migrate on Prem Pyspark, SAS data pipeline and ML Models to Databricks • Define and implement best practices in Databricks • Evaluate new Databricks features and tools, helping the organization stay at the forefront of innovation in AI and Big Data • Collaborate with cross-functional teams to identify and resolve data-related issues. Qualifications: • Proven expertise in implementing Lakehouse and Delta Lake using Databricks. • Strong PySpark and Python experience • Databricks Certified Data Engineer Professional Certification • Familiarity with ML Ops/LLM Ops and distributed systems. • Experience with Big Data platform like Cloudera Hadoop and Could platforms like AWS, GCP. • Solid understanding of system design patterns, scalability, observability, and performance tuning. • Strong analytical and problem-solving skills. • Passion for exploring and building with emerging technologies. Good to Have Skills: • AWS EKS Experience, Dockers and Containers","company":"Covetus","rawCompany":"covetus","city":"Irving","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-06-15T03:49:19.923Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Bricks","description":"Only USC , GC and OPT In-person Interview Job Description Roles & Responsibilities Job Title: Databricks Data Engineer Job Description: As a Databricks Data Engineer, you will be responsible for designing, developing, and maintaining data solutions for data generation, collection, and processing in Big Data environment using predominantly PySpark/Python. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across systems using PySpark. Roles & Responsibilities: • Collaborate closely with data scientists, data engineers, and business stakeholders to gather requirements and understand the business objectives driving data pipeline development. • Design, develop, and maintain robust, scalable high-performance Data Pipelines using Databricks. • Leverage Databricks features such as Lakehouse and Delta Lake for efficient data storage and Spark for distributed processing • Develop ETL/ELT pipeline using Databricks • Monitor pipeline health, troubleshoot data issues • Migrate on Prem Pyspark, SAS data pipeline and ML Models to Databricks • Define and implement best practices in Databricks • Evaluate new Databricks features and tools, helping the organization stay at the forefront of innovation in AI and Big Data • Collaborate with cross-functional teams to identify and resolve data-related issues. Qualifications: • Proven expertise in implementing Lakehouse and Delta Lake using Databricks. • Strong PySpark and Python experience • Databricks Certified Data Engineer Professional Certification • Familiarity with ML Ops/LLM Ops and distributed systems. • Experience with Big Data platform like Cloudera Hadoop and Could platforms like AWS, GCP. • Solid understanding of system design patterns, scalability, observability, and performance tuning. • Strong analytical and problem-solving skills. • Passion for exploring and building with emerging technologies. 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