Senior data engineer

7 days ago

Ahmedabad, India EInfochips Full time
Role: Senior Data Engineer
Years of Experience: 5-10
Location: Ahmedabad
Overview:
We are seeking a highly skilled and experienced Senior Software Engineer to join our Data Engineering team. The ideal candidate will have 5 to 10 years of experience in software engineering, with a strong focus on data engineering practices and an awareness of AI/ML and Generative AI technologies. This role demands proficiency in data processing and analysis, with a keen understanding of both the technical and business aspects of data engineering.
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):
Experience: 5 to 10 years in software/data engineering.
Data Technologies: Proficiency in SQL, No SQL databases (e.g., Dynamo DB, Mongo DB), ETL tools, and data warehousing solutions.
Programming Languages: Proficiency in Python is a must.
Cloud Platforms: Azure, AWS (e.g., EC2, S3, RDS) or GCP.
Visualization Tools: Experience with data visualization tools (e.g., Tableau, Power BI, Looker).
Data Governance: Knowledge of data governance and security practices.
CI/CD: Experience with Dev Ops practices, including CI/CD pipelines and containerization (Docker, Kubernetes).
Communication Skills: Excellent verbal and written communication skills in English.
Agile Methodologies: Experience working in Agile development environments.
AI/ML Awareness: Understanding of AI and ML concepts, frameworks (e.g., Tensor Flow, Py Torch), and practical applications.0
Generative AI Awareness: Familiarity with Generative AI technologies and their potential use cases.
Good to Have Skills:
APIs: Understanding of RESTful APIs and their integration into data workflows.
Advanced Analytics: Knowledge of advanced analytics and statistical techniques.
Microservices: Familiarity with microservices architecture and its implementation.
Data Lakes: Understanding of data lakes and their role in modern data architecture.
Scripting: Proficiency in shell scripting and automation.
AI/ML Deployment: Experience working with and deploying AI/ML models in production environments.
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.

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