The Databricks Data Engineer

Jakub Lasak
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Helping 18k+ Databricks data engineers become seniors: interview like seniors, execute like seniors, think like seniors.

Episódios

  1. The Dashboard Theater: What Databricks Engineers Build That Nobody Opens

    HÁ 8 H

    The Dashboard Theater: What Databricks Engineers Build That Nobody Opens

    You check the usage logs on a dashboard you spent two weeks building. Zero views. Not low views. Zero. The stakeholder who requested it hasn't logged in once. Three months later they ask the exact question the dashboard answers, in a meeting, out loud, as if the dashboard doesn't exist. Because for them, it doesn't. In this episode: - Why the most technically impressive Databricks dashboards are often the least used - The single question senior engineers ask that changes every BI request from ticket to strategic decision - How to spot the three tells of dashboard theater before you commit a single hour - Why a thirty-table automated data quality report got replaced by one Slack message - The taxonomy senior engineers use to price their time: decision instrument, political prop, or habit that doesn't exist yet This episode is for Databricks data engineers who build what stakeholders ask for and wonder why some of it vanishes. Whether you're mid-level trying to understand why your best work goes unnoticed, or senior wanting a named framework for intake conversations, you'll walk away with a diagnostic that saves weeks of invisible work. --- Helping 18,000+ Databricks data engineers become seniors: interview like seniors, execute like seniors, think like seniors. Follow The Databricks Data Engineer for new episodes every Monday, Wednesday, and Friday. LinkedIn: linkedin.com/in/jakublasak Newsletter: dataengineer.wiki #DataEngineering #Databricks #DataEngineer #CareerGrowth #ApacheSpark #DeltaLake

    16 min
  2. The Preparation Gap: What Interviewers Actually Evaluate in Databricks Data Engineers

    6 DE ABR.

    The Preparation Gap: What Interviewers Actually Evaluate in Databricks Data Engineers

    She could explain shuffle hash join versus sort merge join. She knew when Adaptive Query Execution kicks in. She had six weeks of notes on Delta Lake, Spark memory, and cluster configs. She walked into the Databricks senior interview feeling genuinely confident. Then the interviewer asked her to walk through a diagnosis, not recite a definition, and everything she studied was aimed at the wrong target. In this episode: - Why senior Databricks interviews test judgment, not knowledge, and what that means for your prep - The exact moment an interviewer recategorizes you from senior candidate to mid-level - How a debugging scenario exposes the preparation gap in under sixty seconds - Three examples of flipping memorization into scenario-based practice with the same material - The self-assessment that tells you whether your study ratio is working against you This episode is for Databricks data engineers who've been studying hard for a senior interview but aren't confident it's the right kind of preparation. Whether you're building your first study plan or revising one that didn't work last time, you'll walk away knowing exactly how to shift your prep toward what interviewers are actually scoring. --- Helping 18,000+ Databricks data engineers become seniors: interview like seniors, execute like seniors, think like seniors. Follow The Databricks Data Engineer for new episodes. LinkedIn: linkedin.com/in/jakublasak Newsletter: dataengineer.wiki #DataEngineering #Databricks #DataEngineer #CareerGrowth #ApacheSpark #DeltaLake

    16 min
  3. The Invisible Engineer: Why Your Best Work Gets the Least Recognition

    30 DE MAR.

    The Invisible Engineer: Why Your Best Work Gets the Least Recognition

    She kept a terabyte-scale pipeline running for six months without a single incident. Not one page, not one late dashboard. Then review season came and the engineer who spent two weekends fixing an outage he partly caused got the promotion instead. Her name wasn't in a single incident report, because when you prevent problems, there's no report to put your name on. In this episode: - Why the skills Databricks data engineers are hired for produce structurally invisible output - The pattern behind how promotion rubrics reward firefighters and ignore fire preventers - How to keep an incidents-prevented log that turns "nothing broke" into a track record - The communication shift that makes your manager appreciate flawless execution instead of dismissing it as easy - How to frame infrastructure wins in business-outcome language that shows up in reviews This episode is for Databricks data engineers who consistently deliver solid work but feel overlooked at review time. Whether you're mid-level wondering why flashier peers get promoted faster, or senior and tired of your best infrastructure work going unnoticed, you'll walk away with a concrete visibility system you can start this week. --- Helping 18,000+ Databricks data engineers become seniors: interview like seniors, execute like seniors, think like seniors. Follow The Databricks Data Engineer for new episodes every week. LinkedIn: linkedin.com/in/jakublasak Newsletter: dataengineer.wiki Independent educational resource. Not affiliated with or endorsed by Databricks, Inc.

    15 min
  • 3 episódios

Sobre

Helping 18k+ Databricks data engineers become seniors: interview like seniors, execute like seniors, think like seniors.

Informações

  • Criado por
    Jakub Lasak
  • Anos de atividade
    2 mil
  • Episódios
    3
  • Classificação
    Livre
  • Copyright
    © Jakub Lasak
  • Site do podcast
    The Databricks Data Engineer