Advanced proficiency in programming languages commonly used for data engineering (e.g., Python, Java, Scala)

Demonstrated expertise in designing, developing, and optimizing data pipelines for large-scale enterprise environments

Proven experience with corporate dataflows and developing data parsers for extremely large datasets

Extensive experience with various database technologies including graph databases (e.g., Neo4j), SQL databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and vector databases

Familiarity with cloud platforms (AWS, Microsoft Azure) for data storage and processing

Qualifications - Degree from an accredited college or university in System Engineering or related discipline and one of the following: - 10+ years of experience with a Master's degree - 12+ years of experience with a Bachelor's degree - 16+ years of experience with Associate's Degree or HS Diploma

Desired:
Experience with data governance, data security, and compliance best practices

Familiarity with big data technologies such as Hadoop, Spark, or Kafka.

Experience with data warehousing concepts and tools

Continuous learning mindset to stay abreast of cutting-edge data engineering and AI advancements

Understanding of machine learning concepts and their implications for data infrastructure

Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams

Ability to translate complex data requirements into actionable engineering solutions"