Data Engineer

Position: Data Engineer Job Description: Key Responsibilities: - Design, develop, and maintain data pipelines and architectures. - Implement and optimize data integration and transformation processes. - Collaborate with data scientists and machine learning engineers to integrate AI/ML models into data workflows. - Utilize cloud platforms (AWS, GCP, Azure) to deploy and manage data solutions. - Ensure high-quality data ingestion and processing through rigorous testing and validation. - Participate in code reviews to maintain high code quality and standards. - Troubleshoot and debug data engineering solutions, ensuring reliability and performance. - Work with version control systems (preferably git) to manage and maintain codebases. Mandatory Skills (Need Proficiency): 1. Experience: 5 to 10 years in software/data engineering. 2. Data Technologies: Proficiency in SQL, NoSQL databases (e.g., DynamoDB, MongoDB), ETL tools, and data warehousing solutions. 3. Programming Languages: Proficiency in Python is a must. 4. Cloud Platforms: Azure, AWS (e.g., EC2, S3, RDS) or GCP. 5. Visualization Tools: Experience with data visualization tools (e.g., Tableau, Power BI, Looker). 6. Data Governance: Knowledge of data governance and security practices. 7. CI/CD: Experience with DevOps practices, including CI/CD pipelines and containerization (Docker, Kubernetes). 8. Communication Skills: Excellent verbal and written communication skills in English. 9. Agile Methodologies: Experience working in Agile development environments. 10. AI/ML Awareness: Understanding of AI and ML concepts, frameworks (e.g., TensorFlow, PyTorch), and practical applications.0 11. Generative AI Awareness: Familiarity with Generative AI technologies and their potential use cases. Good to Have Skills: 1. APIs: Understanding of RESTful APIs and their integration into data workflows. 2. Advanced Analytics: Knowledge of advanced analytics and statistical techniques. 3. Microservices: Familiarity with microservices architecture and its implementation. 4. Data Lakes: Understanding of data lakes and their role in modern data architecture. 5. Scripting: Proficiency in shell scripting and automation. 6. AI/ML Deployment: Experience working with and deploying AI/ML models in production environments. 7. Big Data Tools: Experience with Hadoop, Spark, Kafka, and other big data technologies. Qualifications : - Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. - Certifications: Relevant certifications in data engineering, cloud platforms, or AI/ML are a plus. Location: IN-GJ-Ahmedabad, India-Ognaj (eInfochips) Time Type: Full time Job Category: Engineering Services