Skills Checklist Builder

Interactive checklists to evaluate candidates or audit your job requirements. Select your hiring need below to get a customizable checklist.

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Skills Checklist for: Airbyte Engineers

12 skills to evaluate candidates

Must Have(Core Requirements)

0/6

Data integration fundamentals

Understanding of data integration concepts: ELT vs ETL, incremental vs full syncs, schema evolution, error handling. Experience with at least one data integration platform (Airbyte, Fivetran, Stitch, or custom pipelines).

Data warehouse experience

Experience with data warehouses (Snowflake, BigQuery, Redshift, Databricks) including loading data, querying, and optimization. Understanding of warehouse architecture and performance.

SQL proficiency

Strong SQL skills for querying data warehouses, writing transformations, and data analysis. Ability to write complex queries and optimize performance.

Error handling and reliability

Experience with error handling, retry strategies, monitoring, and alerting for data pipelines. Understanding of common failure modes and recovery strategies.

Incremental sync patterns

Understanding of incremental sync strategies: timestamp-based, cursor-based, CDC. Ability to design efficient sync patterns that minimize data transfer and costs.

Production experience

Experience deploying data pipelines to production with monitoring, alerting, and observability. Understanding of scale, reliability, and operational requirements.

Nice to Have(Bonus Points)

0/6

Airbyte-specific experience

Direct Airbyte experience including connector configuration, custom connector development, normalization, and Airbyte Cloud/OSS. Accelerates onboarding but learnable quickly.

dbt experience

Experience with dbt for SQL-based data transformations. Understanding of dbt models, tests, and best practices. Important for ELT workflows.

Orchestration tools

Experience with orchestration tools (Airflow, Prefect, Dagster) for managing data pipelines. Understanding of DAGs, scheduling, and dependencies.

Custom connector development

Experience building custom connectors using Airbyte SDK or similar. Ability to integrate proprietary or niche data sources.

Data quality tools

Experience with data quality tools (Great Expectations, dbt tests, custom validation) for ensuring data reliability and correctness.

Python programming

Python skills for custom connector development, data processing scripts, and automation. Useful but not always required.

⚠️ Avoid Over-Emphasizing(Trust Lens)

These requirements often appear in job descriptions but can alienate great developers:

"Airbyte UI knowledge"

Specific Airbyte UI workflows, button locations, or configuration steps are trivial to learn. What matters is understanding data integration patterns, reliability, and integration—skills that transfer across platforms.

"Years of Airbyte experience"

Airbyte launched in 2020 and became widely adopted around 2021-2022. Requiring "5+ years Airbyte experience" is unrealistic. Focus on data integration experience and production data pipeline work, regardless of platform.

"Only Airbyte experience"

Developers skilled with Fivetran, Stitch, or custom pipelines can learn Airbyte quickly. Don't exclude great candidates who've used other data integration tools—the patterns are nearly identical.

"Every data tool"

Airbyte integrates with many data tools, but you don't need expertise in all of them. Focus on the tools you actually use (warehouse, dbt, orchestration).

"Self-hosted infrastructure"

Most Airbyte work uses managed services (Airbyte Cloud) or simple self-hosted setups. Don't require Kubernetes or complex infrastructure experience unless you're running Airbyte at massive scale.