What causes DF-Executor-ExpressionParseError?

A string literal in an expression uses double quotes instead of single quotes — ADF's expression language requires single-quoted string literals. A parameter reference uses `@{pipeline().parameters.name}` syntax (ARM template style) instead of the data flow expression syntax `$paramName`. An expression was edited directly in JSON or copied from another tool, introducing invisible characters or encoding issues that break parsing. A function name is misspelled or used with the wrong number of arguments — ADF expression functions are case-sensitive

How do I fix DF-Executor-ExpressionParseError?

Open the ADF data flow expression builder for the failing transformation and check for syntax errors — look for unclosed parentheses, mismatched quotes, or invalid function names.. The error message names the line or expression that failed to parse; navigate directly to that Derived Column or filter expression.. Validate each function call in the expression against the ADF expression language reference — function names are case-sensitive.. If the expression includes pipeline parameters, verify the parameter syntax: use `$paramName` not `@paramName` in data flow expressions.. Use the expression builder's 'Refresh' button to re-evaluate the expression and see the parse error highlighted in context.

Medium severityconfiguration

Power BI Refresh Error:
DF-Executor-ExpressionParseError

What does this error mean?

An expression in a data flow transformation — a Derived Column, filter, join condition, or aggregate — contains a syntax error that the ADF expression engine cannot parse. The pipeline fails immediately at runtime before any data is processed.

Common causes

1A string literal in an expression uses double quotes instead of single quotes — ADF's expression language requires single-quoted string literals
2A parameter reference uses `@{pipeline().parameters.name}` syntax (ARM template style) instead of the data flow expression syntax `$paramName`
3An expression was edited directly in JSON or copied from another tool, introducing invisible characters or encoding issues that break parsing
4A function name is misspelled or used with the wrong number of arguments — ADF expression functions are case-sensitive

How to fix it

1Open the ADF data flow expression builder for the failing transformation and check for syntax errors — look for unclosed parentheses, mismatched quotes, or invalid function names.
2The error message names the line or expression that failed to parse; navigate directly to that Derived Column or filter expression.
3Validate each function call in the expression against the ADF expression language reference — function names are case-sensitive.
4If the expression includes pipeline parameters, verify the parameter syntax: use `$paramName` not `@paramName` in data flow expressions.
5Use the expression builder's 'Refresh' button to re-evaluate the expression and see the parse error highlighted in context.

Frequently asked questions

The expression looks correct to me — why is it still failing to parse?

Most common hidden cause: ADF expressions require single-quoted string literals, not double quotes. Also check parameter syntax — use `$paramName` in data flow expressions, not `@pipeline().parameters.paramName`. Use the Refresh button to see the highlighted parse error.

Can I copy expressions from one data flow to another?

Yes — copy through the ADF expression builder interface, not JSON. JSON-level copying can introduce encoding issues or miss context-specific column references that exist in one data flow but not another.

Does ExpressionParseError ever occur only on some runs?

No — a parse failure occurs on every run. Inconsistent failures suggest a different error code.

The error says 'line 1, column 47' — how do I find that position in a complex expression?

Open the expression builder for the named transformation and paste the expression. The builder highlights syntax errors inline. The line/column position in the error message refers to the expression text, not the pipeline JSON.

Official documentation: https://learn.microsoft.com/en-us/azure/data-factory/data-flow-troubleshoot-guide