Data Engineer

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Early Applicant

Job Description

Responsibilities

Design, develop, and maintain scalable data pipelines and ETL processes to support analytics and business intelligence initiatives
Implement and optimize data storage solutions, ensuring data quality, accessibility, and security
Collaborate with Data Scientists, Analytics teams, and other stakeholders to understand data requirements and deliver effective solutions
Build and maintain data warehouses and data lakes, ensuring efficient data organization and retrieval
Write clean, maintainable, and well-documented code following team standards and best practices
Participate in code reviews and provide constructive feedback to team members
Monitor and optimize data pipeline performance and efficiency
Create and maintain comprehensive documentation for data processes and architectures
Implement data validation and quality control measures
Contribute to technical discussions and architectural planning sessions
Share knowledge with team members and participate in mentoring activities

Requirements

Required Skills

Bachelor's degree in Computer Science, Data Engineering, or related field
Strong foundation in SQL and experience with relational databases (e.g., PostgreSQL, MySQL)
Proficiency in at least one programming language (e.g., Python, Java, Scala)
Experience with ETL tools and data pipeline development
Understanding of data warehouse concepts and dimensional modeling
Familiarity with version control systems (Git) and collaborative development workflows
Basic knowledge of data security practices and compliance requirements
Strong problem-solving skills and analytical thinking abilities
Excellent communication skills in both technical and non-technical contexts
Demonstrated interest in data engineering through projects or work experience

Preferred Skills

Experience with big data technologies (e.g., BigQuery, Spark)
Knowledge of stream processing frameworks (e.g., Kafka, RabbitMQ)
Experience with data modeling and optimization techniques
Knowledge of data governance principles
Understanding of machine learning pipelines and requirements
Experience with data visualization tools
Understanding of CI/CD practices for data pipelines
Knowledge of scripting languages for automation (e.g., Bash, Shell)
Familiarity with Python web development (e.g., FastAPI, Flask) is a plus
Proficiency with AI-powered coding assistants (e.g., GitHub Copilot, Cursor) is a plus
Familiarity with data warehouse tools or relevant Apache frameworks (e.g., Airflow,Spark)