DEV Community
Career Growth After 35: What Awaits Programmers
DEV Community, Florida, New York, United States
Overview
What expectations, challenges, or opportunities come with career development in the tech industry for programmers 35 and over? The content below provides perspectives on growing a career in tech as you age, including shifting interests toward people, mentoring, teaching, writing, and exploring new areas like AI/ML and data engineering. It emphasizes continuous learning, adapting to changing priorities, and remaining active in coding while expanding influence through teaching, mentoring, and thought leadership. Responsibilities and activities
Learn, grow, and invest in others and yourself; continue to build skills as technology evolves. Mentor and teach others, including moving into roles such as instructors or bootcamp mentors, and contribute to OSS projects. Write, create courses, present at conferences, and share knowledge to impact organizations and peers. Maintain coding practice while influencing teams through process improvement and high-quality software delivery. Adapt to new domains (e.g., AI/ML, data engineering) and translate technical work into practical products or services. Paths and pathways
Many engineers continue to code at senior levels, and some build products or SaaS, while others move into consulting or advisory roles. Management is one possible path but not the only one; there are senior individual contributor tracks, teaching/mentoring roles, and cross-disciplinary roles that combine development with leadership or strategy. Agencies and non-traditional environments may have different progression dynamics; preparation and ongoing learning remain important across settings. Qualifications and mindset
Key themes include a commitment to lifelong learning, the ability to collaborate with people of diverse ages, and openness to changing career directions based on interest and opportunity. Staying curious, focused, and proactive in skill development is highlighted as essential regardless of age. Examples and experiences
Examples from the content include transitioning into data engineering, leading as a data engineer, writing and teaching, and continuing to code while improving processes and efficiency. The discussions emphasize that significant career growth is possible after 35, 45, or even 75 with the right focus and attitude.
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What expectations, challenges, or opportunities come with career development in the tech industry for programmers 35 and over? The content below provides perspectives on growing a career in tech as you age, including shifting interests toward people, mentoring, teaching, writing, and exploring new areas like AI/ML and data engineering. It emphasizes continuous learning, adapting to changing priorities, and remaining active in coding while expanding influence through teaching, mentoring, and thought leadership. Responsibilities and activities
Learn, grow, and invest in others and yourself; continue to build skills as technology evolves. Mentor and teach others, including moving into roles such as instructors or bootcamp mentors, and contribute to OSS projects. Write, create courses, present at conferences, and share knowledge to impact organizations and peers. Maintain coding practice while influencing teams through process improvement and high-quality software delivery. Adapt to new domains (e.g., AI/ML, data engineering) and translate technical work into practical products or services. Paths and pathways
Many engineers continue to code at senior levels, and some build products or SaaS, while others move into consulting or advisory roles. Management is one possible path but not the only one; there are senior individual contributor tracks, teaching/mentoring roles, and cross-disciplinary roles that combine development with leadership or strategy. Agencies and non-traditional environments may have different progression dynamics; preparation and ongoing learning remain important across settings. Qualifications and mindset
Key themes include a commitment to lifelong learning, the ability to collaborate with people of diverse ages, and openness to changing career directions based on interest and opportunity. Staying curious, focused, and proactive in skill development is highlighted as essential regardless of age. Examples and experiences
Examples from the content include transitioning into data engineering, leading as a data engineer, writing and teaching, and continuing to code while improving processes and efficiency. The discussions emphasize that significant career growth is possible after 35, 45, or even 75 with the right focus and attitude.
#J-18808-Ljbffr