BIG DATA SOFTWARE ENGINEER SKILLS, EXPERIENCE, AND JOB REQUIREMENTS
Updated: Sep 21, 2024 - The Big Data Software Engineer brings a rich blend of skills, including expertise in various database management systems and proficiency with tools like Git and JetBrains IDE products. This role demands a strong foundation in agile methodologies, machine learning applications, and the ability to develop software for biomedical sciences and bioinformatics. This position's competencies include extensive experience in Linux, knowledge of statistics and genomics, and a firm grasp on object-oriented design, ETL tools, and advanced data processing techniques.
Essential Hard and Soft Skills for a Standout Big Data Software Engineer Resume
- Programming Languages
- Big Data Frameworks
- Database Management
- Data Warehousing
- ETL Tools
- Data Modeling
- Cloud Computing
- Machine Learning
- Data Visualization
- Data Security
- Analytical Thinking
- Problem-Solving
- Attention to Detail
- Communication
- Collaboration
- Adaptability
- Time Management
- Creativity
- Curiosity
- Critical Thinking
Summary of Big Data Software Engineer Knowledge and Qualifications on Resume
1. BS in Computer Science with 3 years of experience
- Strong Background in Data warehousing principles, architecture and its implementation in large environments.
- Experience in data engineering applications and products in AWS or any cloud provider.
- Data engineering/ETL Design and Development knowledge using Hadoop or Spark
- Experience with AWS (Dynamo DB, Lambda, or S3).
- Hands-on experience on programming (Java, Python, or Scala), and performing data/file manipulation using Shell scripting.
- Experience using no-SQL technologies and Big Data platforms - strong development skills around Hadoop, Hive, Map Reduce.
- Hands-on experience using Database procedural languages such as SQL, PL/SQL, T-SQL
- Experience working in Agile/SCRUM model.
- Experience with TS//SCI with CI or FSP polygraph
2. BS in Information Technology with 5 years of experience
- Experience with one or more of the following: Python, Java, Elasticsearch, Spark, Kafka, Hadoop.
- Experience in API design, authoring and consuming web services, utilizing relational and NoSQL databases, and distributed data storage, processing and query platforms.
- Experience with Agile software development, Scrum, Git/GitHub and software development lifecycle (SDLC)
- Self-starter with an ability to work independently and in a collaborative team environment including on a government site
- Strong problem-solving, critical thinking, and analysis skills.
- Ability to articulate complex analytic problems, work effectively without detailed instructions, collaborate and ask questions.
- Demonstrated interest and/or experience with AI/ML, including algorithm, evaluation and optimization
- Experience with network data (IP traffic), internet protocols, telecommunications data
- Experience with Bro/Zeek, TShark/PyShark, or other network analysis tools
- Experience with C/C++, MongoDB, Docker, AWS, Linux/CentOS
3. BS in Software Engineering with 2 years of experience
- Experience with a variety of database management systems beyond relational databases
- Experience with operational tools such as Git, JetBrains IDE products (PyCharm, Idea), CI Tools such as Jenkins or Bamboo, Atlassian Suite
- Experience with and capable of working in an agile development environment
- Experience or knowledge with machine learning applications at scale
- Experience in identifying and developing software applications in the biomedical sciences and/or bioinformatics and implementing systems for analyzing large-scale scientific data
- Strong knowledge of Linux environments
- Knowledge in statistics, biology, genomics
- Hands-on experience with test practices and processes, test automation, test coverage and user acceptance testing.
- Exposure to Object-oriented design, distributed computing, performance/scalability tuning, advanced data structures and algorithms, real-time analytics and large-scale data processing.
- Exposure to ETL Development tools such as Airflow, SSIS, SSRS, and DataServices.