| Senior Data Engineer at Richardson, Texas, USA |
| Email: [email protected] |
| Job Title: Senior Data Engineer Location: Richardson, TX, Candidates will work in-office 3 days per week Hybrid role Send only locals to TX consultants Experience :10+ Years Rate : 57.5$/hr on C2C Fixed Description This person will be responsible for building new Data Pipelines to extract & transfer data. There will then be an ML Engineer that will deploy the models you create. We are seeking an experienced Senior Data Engineer with a strong background in Python, SQL, and Azure Cloud technologies. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support our growing data needs. You will collaborate closely with data scientists, analysts, and other engineering teams to ensure data availability, integrity, and performance. Required: 6+ years in advanced SQL 6+ years in advanced Python Scheduling Tool(s): Apache Airflow or Kubeflow (either will work) Azure (preferred), GCP, or AWS advanced Public Cloud Experience Proficiency in Python for data manipulation, automation, and scripting. Advanced SQL skills for complex query writing, optimization, and database management. Experience with Azure Kubernetes. Experience with big data technologies (e.g., Spark, Hadoop) and data lake architectures. Familiarity with CI/CD pipelines, version control (Git), and containerization (Docker) is a plus. Key Responsibilities: Data Pipeline Development:** Design, develop, and maintain robust ETL/ELT, curated and feature engineering processes using Python and SQL to extract, transform, and load data from various sources into our data platforms. Database Management:** Optimize, manage, and monitor SQL databases and data warehouses, ensuring high performance and efficient data retrieval. Data Integration:** Work with both structured and unstructured data sources to integrate diverse data sets into a unified, accessible format. Data Quality and Governance:** Implement data quality checks, validation procedures, and data governance standards to maintain data accuracy and consistency. Collaboration:** Collaborate with cross-functional teams, including data scientists, data analysts, software engineers, and product managers, to define data requirements and deliver solutions that meet business needs. Performance Tuning:** Optimize performance of large-scale data processing systems and databases to ensure efficient data access and usage. Documentation:** Create and maintain comprehensive documentation for data engineering processes, architectures, and pipelines. Innovation:** Stay up-to-date with the latest trends and technologies in data engineering and cloud services, recommending and implementing new tools and techniques as appropriate. Thanks and Regards Raju Akurathi | IT Ideology | SR Business Development Specialist Email ID: [email protected] www.itideology.com -- Keywords: continuous integration continuous deployment machine learning information technology Idaho Texas Senior Data Engineer [email protected] |
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| Thu Sep 05 21:18:00 UTC 2024 |