Designs and optimizes large-scale data pipelines and parsers using Python, Java, Scala, and various databases (SQL, NoSQL, graph, vector) for enterprise clients.
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"