Senior Data Engineer

The Senior Data Engineer plays a pivotal role in the design, development, and optimization of robust data pipelines and infrastructure that power AI-driven and data-intensive applications.

• Design, develop, and maintain scalable, efficient, and secure ETL (Extract, Transform, Load) pipelines.
• Build real-time and batch data processing frameworks for AI, analytics, and business intelligence.
• Optimize data storage, retrieval, and performance across structured and unstructured data sources.

• Implement data governance frameworks, ensuring data integrity, consistency, and compliance with security standards.
• Monitor and enforce best practices for data privacy, encryption, and regulatory compliance (GDPR, CCPA, etc.).
• Work closely with Data Scientists and Machine Learning Engineers to support AI model training, inference, and deployment.
• Partner with Dev Ops teams to automate data workflows and ensure smooth integration with cloud platforms.
• Act as a liaison between business stakeholders and technical teams, translating business needs into data solutions.

• Continuously optimize data infrastructure for performance, reliability, and scalability.
• Implement monitoring solutions to detect and resolve data pipeline issues proactively.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 3+ years of experience in data engineering, including ETL pipeline development.
• Expertise in SQL and No
  
  SQL databases (Postgre
  
  SQL, Mongo
  
  DB, Cassandra, etc.).
• Proficiency in big data technologies such as Apache Spark, Kafka, and Hadoop.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and data warehousing (Big Query, Snowflake, Redshift).
• Strong knowledge of data orchestration tools (Airflow, Prefect, or similar).
• Experience with data security best practices and compliance requirements.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.