Data Engineer

Company Overview

(Company overview details not provided.)

Job Summary

The Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure. This role is integral to ensuring that data is accessible, reliable, and prepared for analysis, thus contributing to the organization’s data-driven decision-making processes.

Responsibilities

• Design, develop, and maintain robust data pipelines to support data ingestion, transformation, and storage.
• Collaborate with data scientists and analysts to understand data requirements and ensure optimal data flow.
• Perform data quality checks and ensure the integrity and accuracy of data throughout the pipelines.
• Optimize SQL queries and Python scripts for performance and efficiency.
• Monitor and troubleshoot data pipeline issues to ensure continuous data availability.
• Document processes and maintain data flow diagrams for reference and compliance.

Qualifications

• Technical Skills:
  • Strong proficiency in SQL for data analysis and database management.
  • Proficient in Python programming for data manipulation and automation.
• Soft Skills:
  • Excellent problem-solving skills and attention to detail.
  • Strong communication skills for collaboration with cross-functional teams.
• Educational Qualifications:
  • Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Experience:
  • Minimum of 9 years of experience in data engineering or a related field.

Preferred Skills

• Experience with big data technologies such as Hadoop, Spark, or Kafka.
• Familiarity with cloud data platforms like AWS, Google Cloud, or Azure.
• Knowledge of data warehousing concepts and ETL processes.

Experience

• A minimum of 9 years of relevant experience in data engineering or related roles.

Environment

• This is a full-time position with an immediate start date. The specific work setting (remote, in-office, hybrid) has not been specified.

Salary

(Salary details not provided.)

Growth Opportunities

(Potential career advancement opportunities not provided.)

Benefits

(Benefits details not provided.)