Podcast
Data Engineering Job Prep & Interview Guide: Python, SQL, Portfolio & Job Search Tips
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Data Engineering Job Prep & Interview Guide: Python, SQL, Portfolio & Job Search Tips
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Episode Overview
How do you actually get a data engineering job today — and which skills hiring teams care about most? In this episode, Jeff Katz, a Machine Learning Engineer at AppFolio and longtime instructor/founder of Jigsaw Labs and Flatiron School curriculum lead, distills a webinar on hiring demand into practical advice for job seekers. Drawing on applied AI and data engineering experience plus open-source contributions, Jeff walks through the core data engineering skills employers expect: deep Python and SQL, Docker,.
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Chapter Summary
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- 0:00 - Podcast Introduction
- 0:36 - Webinar Recap: Hiring Demand and Skill Gaps
- 1:20 - Core Skills & Tools: Python, SQL, Docker, Airflow, Data Warehouses
- 1:49 - Python & SQL Depth: Project Volume and Emphasis
- 2:22 - Code Quality & OOP: Small Functions, Classes, Tests
- 2:46 - Portfolio Strategy: Personal Projects and Open Source Contributions
- 3:38 - Application Funnel: LinkedIn, Resume, and Interview Stages
- 5:15 - Behavioral Interview Best Practices: Positivity, Structure, Motivation
- 7:46 - Technical Interview Formats: SQL LeetCode, Python Problems, Take-Home Projects
- 9:41 - Core Database Concepts: Views, Materialized Views, OLTP vs OLAP
- 11:24 - Learning Resources: Python Books, Flask Mega-Tutorial, SQL Platforms
- 14:11 - BI to Data Engineering Transition: Upskilling Within Your Role
- 15:53 - Job Search Strategy: Apply Broadly and Avoid Self-Filtering
- 16:48 - Leveraging Non-Coding Experience and Domain Expertise
- 19:57 - Role Differentiation: Data Analyst vs Data Engineer
- 21:56 - Certifications vs Skills: When Certificates Help and When They Don’t
- 23:13 - Master’s Degree Trade-offs: Research Depth vs Applied Learning
- 27:46 - Remote Work Reality: Timezones, Legal Constraints, and Standout Candidates
- 30:06 - Teaching & Coaching on Resume: Communication and Mentorship Value
- 32:22 - OOP Relevance: Patterns for Airflow and Maintainable Code
- 33:03 - Language Choices: Python Focus; Java/Scala and Spark Considerations
- 35:09 - Interview Load: Typical Number and Style of Technical Questions
- 37:49 - Cloud Certification Prep: Learning Fundamentals vs Credential Hunting
- 39:49 - Commercial Experience Alternatives: Nonprofits, Contract Work, Internships
- 43:31 - Mid-Career Switch: Sales Skills as an Asset in Tech Hiring
- 46:16 - Solution Engineer Pathway: Pre-/Post-Sales Roles as Transition Options
- 47:26 - Episode Wrap-Up and Further Resources