Data Management Developer

Develop and maintain data pipelines using PySpark to process and transform large volumes of data.

Design, implement, and optimize data solutions using DataBricks for data analytics and machine learning applications.

Manage and administer cloud-based data platforms such as Snowflake and Redshift, ensuring high availability, scalability, and performance.

Collaborate with cross-functional teams to understand data requirements and deliver tailored data solutions.

Implement data governance policies and procedures to ensure data quality, consistency, and security.

Monitor and troubleshoot data issues, ensuring timely resolution and minimal impact on business operations.

Stay updated with the latest trends and technologies in data management, cloud computing, and big data analytics.

Provide technical guidance and mentorship to junior data management team members.

Qualifications

Bachelor's degree in Computer Science, Information Systems, or related field; Master's degree preferred.

Minimum of 5 years of experience in data management, data engineering, or related role.

Strong programming skills in Python and experience with PySpark for data processing and analytics.

Hands-on experience with DataBricks for building and optimizing data pipelines.

Proficiency in managing and administering cloud-based data platforms such as Snowflake and/or Redshift.

Solid understanding of data modeling, ETL processes, and data warehousing concepts.

Excellent analytical, problem-solving, and communication skills.

Ability to work effectively in a fast-paced environment and manage multiple priorities.

Preferred Qualifications

Certifications in PySpark, DataBricks, Snowflake, or Redshift.

Experience With Other Data Management Tools And Technologies.

Knowledge of machine learning algorithms and techniques.