Career Paths for Software Professionals
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This document outlines various career paths for software professionals, including software development, quality engineering, project management, UI/UX design, business analysis, databases and data warehousing, big data, data science, security, agile coaching, DevOps, IT administration, embedded systems, and academic careers. It provides descriptions of common roles within each path as well as typical career progression charts. The data science section in particular outlines technical skills, responsibilities, and example tasks required of data scientists. Overall, the document serves to inform software professionals about options for specializing and advancing their careers.
Career Paths for Software Professionals
- 1. Career Paths for Software Professionals Ahmed Misbah
- 2. Main Career Paths âą Software Development âą Quality Engineering âą Project Management âą UI/UX Design âą Business Development âą Business Analysis âą Databases and Data Warehousing âą Big Data âą Data Science âą Security âą Agile Couching âą DevOps âą IT Administration âą Embedded Systems âą Academic Career
- 3. Software Development âą Open-source technologies based on known programming languages âą Product/Technology Consultant: â Microsoft â Oracle â IBM â SAP
- 5. Software Development âą Full Stack Developer âą Web Developer âą Mobile Developer âą Backend Developer âą Integrator/Middleware
- 6. Software Development Associate/Trainee Software Developer Software Developer Senior Software Developer Associate Technical Lead Technical Lead Senior Technical Lead Associate Architect Architect Senior Architect VP Software Development Corporate Management
- 7. Quality Engineering âą Quality Control Engineer: â Manual Testing Engineer â Test Automation Engineer â Performance Testing Engineer âą Quality Assurance Engineer: monitors the software engineering processes and methods used to ensure quality âą Software Engineer In Test (SeT)
- 8. Quality Engineering Associate/Trainee Quality Engineer Quality Engineer Senior Quality Engineer Associate Quality Lead Quality Lead Senior Quality Lead Consultant Specialized Service Consultant Service Manager VP Specialized Services Corporate Management Business Consultant Product Manager VP Product Management Corporate Management
- 9. Project Management Management Trainee Associate Project Manager Project Manager Senior Project Manager Associate Delivery Manager Delivery Manager Senior Delivery Manager VP Product Delivery Corporate Management
- 10. UI/UX Design Associate/Trainee UX Engineer UX Engineer Senior UX Engineer Associate UX Lead UX LeadSenior UX LeadConsultant UX Consultant UX Research Consultant HoD UX R&D VP R&D Corporate Management CA/Marketing Consultant Sales Development Manager VP Marketing Corporate Management
- 12. Business Analysis Associate/Trainee Business Analyst Business Analyst Senior Business Analyst Associate Business Consultant Business Consultant Senior Business Consultant Associate Product Manager Product Manager Senior Product Manager VP Product Management Corporate Management
- 13. Databases and Data Warehouses âą DB Developer âą DB Administrator âą Data Warehouse Engineer
- 14. Big Data âą Big Data Developer: â Apache Hadoop â Apache Spark â Apache Flink â Apache Storm â Apache Kafka â Apache Cassandra â Cloudera â Datastax â Hortonworks â Splunk âą Big Data Administrator
- 15. Data Science âą Data scientists are big data wranglers. They take an enormous mass of messy data points (unstructured and structured) and use their formidable skills in math, statistics and programming to clean, massage and organize them. Then they apply all their analytic powers â industry knowledge, contextual understanding, skepticism of existing assumptions â to uncover hidden solutions to business challenges.
- 16. Data Science A Data Scientist may be required to: âą Conduct undirected research and frame open- ended industry questions âą Extract huge volumes of data from multiple internal and external sources âą Employ sophisticated analytics programs, machine learning and statistical methods to prepare data for use in predictive and prescriptive modeling âą Thoroughly clean and prune data to discard irrelevant information
- 17. Data Science âą Explore and examine data from a variety of angles to determine hidden weaknesses, trends and/or opportunities âą Devise data-driven solutions to the most pressing challenges âą Invent new algorithms to solve problems and build new tools to automate work âą Communicate predictions and findings to management and IT departments through effective data visualizations and reports âą Recommend cost-effective changes to existing procedures and strategies
- 18. Data Science Technical Skills: âą Math (e.g. linear algebra, calculus and probability) âą Statistics (e.g. hypothesis testing and summary statistics) âą Machine learning tools and techniques (e.g. k-nearest neighbors, random forests, ensemble methods, etc.) âą Software engineering skills (e.g. distributed computing, algorithms and data structures) âą Data mining âą Data cleaning âą Data visualization (e.g. ggplot and d3.js) and reporting techniques âą Unstructured data techniques âą R languages âą SQL databases and database querying languages âą Python (most common), C/C++, Java, Perl âą Big data platforms like Hadoop âą Cloud tools like Amazon S3
- 19. Security
- 20. Agile Couching âą Iteration Manager/Scrum Master âą Agile Couch/Consultant
- 21. DevOps Engineer / Site Reliability Engineer
- 22. IT Administration Associate/Trainee IT Support Engineer IT Support Engineer Senior IT Support Engineer Associate IT Support Lead IT Support Lead Senior IT Support Lead Associate IT Manager IT Manager Senior IT Manager VP MIS Corporate Management
- 23. Embedded Systems Technical Skills: âą Excellent coding skill in hardware-related C programming âą Experience doing low-level optimization in C assembly âą Experience with Git or other source code management system âą Experience with embedded Linux kernel configuration and device driver development âą Skilled in specialized techniques for embedded programming, such as debouncing switches âą Able to read electronics schematics and troubleshoot problems âą Able to use an oscilloscope, multimeter, soldering iron and other basic electronics equipment âą killed in Java and Android development âą Able to use Perl or Python for scripting, for example when modifying simple text files âą Have a solid understanding of the software development and project management life cycle
- 24. Academic Career
- 25. Academic Career
- 26. Choosing the best path which suites you! âą Seek where your passion is⊠⹠Assess your competencies⊠⹠Work on the required core competencies⊠⹠Test your personality⊠⹠Accept the challenge, never judge without trying⊠⹠Never fear to switch paths⊠⹠Look up to a role model and be inspiredâŠ.