Key Responsibilities:

Collaborate with cross-functional teams to understand data requirements and design efficient data pipelines.
Develop, implement, and maintain ETL (Extract, Transform and Load) processes to collect, clean, and store data from various sources.
Optimize and enhance existing data pipelines for better performance, scalability, and reliability.
Ensure data quality and integrity through data validation, monitoring, and error handling.
Troubleshoot and resolve data-related issues in a timely manner.
Collaborate with data scientists and analysts to provide them with the necessary data sets and tools to perform advanced analytics and reporting.
Implement data security and privacy best practices to protect sensitive information.
Stay updated with the latest trends and technologies in data engineering and contribute to the continuous improvement of our data infrastructure.

Skills & Qualifications:

Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent work experience).
3+ years of experience in data engineering or a related role.
Proficiency in programming languages such as Python, Java, or Scala.
Strong experience with data warehouse technologies (e.g., AWS Redshift, Google BigQuery, Snowflake).
Hands-on experience with ETL tools and frameworks (e.g., Apache Spark, Apache NiFi).
Knowledge of database systems (SQL and NoSQL) and data modeling.
Familiarity with data integration and orchestration tools (e.g., Apache Airflow).
Understanding of data security and compliance standards
Excellent problem-solving and communication skills.
Ability to work independently and collaboratively in a fast-paced environment.
Strong attention to detail and a commitment to delivering high-quality work.
Experience with version control systems (e.g., Git).
Certification in relevant data engineering technologies.