The DA/DE line has blurred: dbt Labs' 2026 State of Analytics Engineering report shows analysts increasingly own their own pipelines. This guide reflects that. SQL and stakeholder skills are still the core, but GitHub, dbt and pipeline literacy are no longer "nice to have." That doesn't mean becoming a data engineer; it means knowing enough to be self-sufficient and to collaborate without creating work for the DE team.
AI-assisted SQL and text-to-SQL copilots, and tools like Snowflake Cortex, BigQuery's Gemini integration and Databricks' AI/BI Genie, are increasingly standard. Use them to go faster on the mechanical part (writing the query), never to skip the judgement part (deciding the query is the right one to ask, and that the result is trustworthy). Interviewers in 2026 are explicitly testing for the second half. See the AI in Data section for more on using these well.
BigQuery sandbox, Google Colab and DuckDB: full detail in the Free Tool Directory doc.