IBM is hiring a Data Engineer Data Platforms group in a far-off potential. The function includes designing, building, and keeping scalable statistics pipelines, optimizing facts workflows, and supporting records infrastructure for various enterprise applications. Ideal candidates must have information in cloud platforms, records integration, and programming languages like Python or Java. Strong problem-solving skills and experience with big data equipment are required. Competitive profits and benefits bundle supplied.
- Job Role: Data Engineer Data Platforms (Remote)
- Salary: Not Disclosed
- Location: Gurugram, Haryana
- Company: IBM
- Qualification: No Degree Mentioned
- Experience: 6+ years
ABOUT IBM
IBM (International Business Machines Corporation) is an international generation and consulting business enterprise, based in 1911. Headquartered in Armonk, New York, IBM is a leader in the fields of synthetic intelligence, cloud computing, information analytics, quantum computing, and organization answers. With a wealthy record of innovation, IBM has developed leap-forward technology, which includes the IBM mainframe, Watson AI, and IBM Cloud.
The corporation serves an extensive variety of industries, providing contemporary products and services designed to force digital transformation, enhance enterprise operations, and decorate purchaser stories. IBM’s assignment is to create a fee for its clients by combining advanced era with deep enterprise expertise. The employer is committed to sustainability, range, and advancing the destiny of work. With a focal point on research and development, IBM continues to shape the era panorama, supporting businesses around the arena to adapt to an ever-evolving virtual generation.
Job Description:
We are looking for a professional Data Engineer to join our team remotely, focusing on building and maintaining robust information platforms. The best candidate will format and implement scalable data pipelines, optimize data storage, and ensure seamless integration with various structures. Proficiency in Python, SQL, cloud era (AWS, GCP, or Azure), and statistics warehousing is needed. The role includes taking elements with go-purposeful groups to make sure statistics are accessible, exceptional, and secure. Strong hassle-fixing competencies a revel in ETL processes, and an ardor for working with large datasets are essential.
Key Responsibilities Data Engineer Data Platforms (Remote):
- Data Pipeline Development: Design, build, and keep efficient and scalable ETL (Extract, Transform, Load) pipelines to system big volumes of based totally and unstructured data from numerous belongings.
- Data Integration: Work with pass-practical teams to mix records throughout multiple systems, making sure seamless records drift and compatibility during systems.
- Data Quality & Integrity: Monitor and ensure the accuracy, completeness, and consistency of records across the commercial enterprise organization, enforcing automatic facts high-quality tests, and validation approaches.
- Database Management: Design and optimize relational and non-relational databases, making sure immoderate-normal performance data garage and retrieval. Optimize query overall performance and decrease bottlenecks.
- Collaboration: Collaborate with information scientists, analysts, and product groups to recognize statistics requirements and provide information answers that align with commercial enterprise goals.
- Documentation & Best Practices: Maintain complete documentation for statistics architectures, workflows, and strategies. Promote nice practices in information engineering, ensuring the team adheres to great coding standards and tips.
- Performance Optimization: Continuously enhance the overall performance of records systems with the aid of satisfactory-tuning facts processing workflows and garage mechanisms to deal with large datasets efficiently.
Key Skills:
- Programming Languages: Strong skills in Python, Java, or Scala for constructing statistics pipelines and automation scripts.
- SQL: Expertise in writing complex SQL queries, optimizing queries, and operating with relational databases that incorporate MySQL, PostgreSQL, or SQL Server.
- Cloud Platforms: Experience with cloud computing structures like AWS, Azure, or Google Cloud, including offerings like S3, Redshift, BigQuery, and Data Lake.
- Data Warehousing: Hands-on revel in records warehousing principles and equipment, together with designing statistics lakes, megastar schemas, and partitioning techniques.
- Data Modeling: Knowledge of designing green data fashions for large datasets, making sure of scalability and average overall performance.
- Problem Solving & Troubleshooting: Strong analytical abilities with the capability to troubleshoot complicated data problems and optimize machine ordinary overall performance.
- Communication: Ability to surely speak technical thoughts to non-technical stakeholders and collaborate successfully with circulate-functional groups.
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