Data Engineer

About Us:

We are a global AI company dedicated to delivering innovative enterprise solutions by integrating cutting-edge technology into our products. We value creativity, innovation, and collaboration, and we are looking for a skilled Data Engineer to join our team.

Role Overview:

As a Data Engineer at our company, you will be responsible for designing, building, and maintaining the data infrastructure that powers our AI/ML models. You will work closely with data scientists, product teams, and other stakeholders to ensure seamless data flow and high-quality outputs. Your expertise in ETL processes, data warehousing, and cloud technologies will be crucial to our success.

Key Responsibilities:

• Data Pipeline Design: Architect and implement efficient data pipelines for extracting, transforming, and loading (ETL) data from various sources.
• Data Integrity & Security: Ensure the integrity, security, and compliance of data across all systems, adhering to organizational standards.
• Performance Optimization: Optimize data processing workflows for speed, scalability, and cost-effectiveness.
• Cross-functional Collaboration: Work with data scientists to understand their requirements and provide reliable datasets for model training and deployment.
• Problem-Solving: Troubleshoot issues in data pipelines, databases, or ETL processes, ensuring minimal downtime and high availability.
• Documentation & Communication: Maintain detailed documentation of data systems, pipelines, and processes. Communicate technical details to non-technical stakeholders effectively.
• Stay Updated: Keep up with emerging trends in data engineering tools, technologies, and best practices.

Requirements:

• Proficiency in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB).
• Strong understanding of ETL processes and tools like Apache Nifi, Talend, or Airflow.
• Experience with cloud-based data platforms (AWS, Azure, GCP) for data storage and processing.
• Familiarity with distributed computing frameworks such as Hadoop, Spark, or Dask.
• Knowledge of data warehousing concepts and tools like Snowflake, Redshift, or BigQuery.
• Bachelor’s/Master’s degree in Computer Science, Data Engineering, or a related field.
• Strong problem-solving skills and attention to detail.
• Excellent communication skills to collaborate effectively with cross-functional teams.
• Flexibility to align with global team collaboration and meeting schedules.

Nice-to-Have:

• Certifications in cloud platforms (AWS Certified Solutions Architect, Google Cloud Professional Data Engineer).
• Contributions to open-source projects or experience with DevOps practices.
• Experience with real-time data processing frameworks like Kafka or Flink.

Why Join Us?

• Opportunity to work on large-scale data systems that power AI/ML innovations.
• Collaborative and innovative work environment.
• Flexible remote work arrangements.
• Professional growth and development opportunities.