Senior Data Scientist (Senior Software Developer; Systems Software)
About The Position
This role requires advanced proficiency in programming languages for data engineering, such as Python, Java, and Scala. The ideal candidate will have 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 is essential. The position also demands 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 like AWS and Microsoft Azure for data storage and processing is also required.
Requirements
- 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.
- Degree from an accredited college or university in System Engineering or related discipline.
- 10+ years of experience with a Master's degree OR 12+ years of experience with a Bachelor's degree OR 16+ years of experience with Associate's Degree or HS Diploma.
- Excellent communication and interpersonal skills.
- Ability to translate complex data requirements into actionable engineering solutions.
Nice To Haves
- 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.
Responsibilities
- Design, develop, and optimize data pipelines for large-scale enterprise environments.
- Develop data parsers for extremely large datasets.
- Utilize expertise in various database technologies including graph, SQL, NoSQL, and vector databases.
- Leverage cloud platforms (AWS, Microsoft Azure) for data storage and processing.
- Translate complex data requirements into actionable engineering solutions.
- Collaborate effectively with cross-functional teams.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
