Krise Hiring! Full Time DATA ENGINEER in - Ricebowl

Job Summary

We are looking for a skilled and detail-oriented Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure. You will work closely with data scientists, analysts, and business teams to ensure the availability, reliability, and accuracy of data.

Responsibilities

• Design, build, and optimize scalable data pipelines for data extraction, transformation, and loading (ETL/ELT) to support business analytics and operations
• Develop and maintain data architectures, databases, and data warehouses to ensure efficient data storage and retrieval
• Collaborate with data scientists and analysts to understand data requirements and deliver clean, structured datasets for analysis
• Monitor and improve the performance and reliability of data systems to maintain high availability
• Implement and enforce data quality, security, and governance practices to comply with privacy and regulatory standards
• Manage data storage and processing using cloud platforms such as AWS, Azure, or GCP to enable scalable solutions
• Automate data workflows and processes using orchestration tools like Airflow to increase operational efficiency
• Maintain comprehensive documentation of data models, schemas, and system configurations for transparency and knowledge sharing

Required competencies and certifications

• Proven 2+ years of experience as a Data Engineer or in a similar role
• Proficient in programming languages such as Python, Scala, or Java for data engineering tasks
• Strong SQL skills and experience working with relational and NoSQL databases including PostgreSQL, MySQL, and MongoDB
• Hands-on experience with ETL tools and data pipeline frameworks such as Apache Spark, Kafka, and Airflow
• Experience with cloud data platforms including AWS (Redshift, Glue, S3), Azure (Data Factory, Synapse), or GCP (BigQuery, Dataflow)
• Familiarity with data modeling, data warehousing concepts, and data lakes to support scalable data solutions
• Experience with big data technologies like Hadoop, Hive, or Presto for processing large datasets
• Knowledge of CI/CD and DevOps practices applied to data engineering for continuous integration and deployment
• Experience using version control tools such as Git to manage code and collaboration
• Understanding of data privacy and compliance standards such as GDPR and HIPAA to ensure secure data handling

Preferred competencies and qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field