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Role Roadmap

Data Engineer

Design and run distributed data pipelines, lakehouses, and streaming systems.

7 technologies in this stack — ordered Core → Edge → Hybrid bonus. Click any tile to start practicing.

Core

Core — lands the role. Baseline skills hiring managers screen for. Master these and you can land the role at market CTC.

Edge

Edge — lifts your CTC band. Rarer skills that strengthen negotiation — they can push the offer toward the top of the band (e.g. ₹30–40L+ for senior data roles).

Hybrid bonus

Hybrid bonus — broadens your profile. Cross-domain extras (e.g. Power BI for a Data Engineer) that open hybrid roles and raise your profile weightage with recruiters.

  1. Core
    1

    Databricks

    Unity Catalog, Delta Live Tables, Workflows, MLflow, and Lakehouse architecture.

    Open practice tracks →
  2. Core
    2

    Apache PySpark

    Distributed data processing with Python and Apache Spark — the most asked skill in data engineering interviews.

    Open practice tracks →
  3. Core
    3

    SQL & Advanced SQL

    Query optimization, window functions, CTEs, and complex joins. Asked in every data role.

    Open practice tracks →
  4. Edge
    4

    Apache Kafka

    Event streaming, producer/consumer patterns, partitioning, exactly-once semantics.

    Open practice tracks →
  5. Edge
    5

    Apache Airflow

    DAG design, operators, sensors, TaskFlow API, scheduling, and production debugging.

    Open practice tracks →
  6. Hybrid bonus
    6

    dbt (Data Build Tool)

    Models, tests, macros, incremental strategies, and CI/CD for data transformation.

    Open practice tracks →
  7. Hybrid bonus
    7

    Snowflake

    Virtual warehouses, clustering, Time Travel, Streams, Tasks, and cost optimization.

    Open practice tracks →