diff --git a/metadata-integration/java/acryl-spark-lineage/README.md b/metadata-integration/java/acryl-spark-lineage/README.md
index f619c77862..27da37ca79 100644
--- a/metadata-integration/java/acryl-spark-lineage/README.md
+++ b/metadata-integration/java/acryl-spark-lineage/README.md
@@ -1,7 +1,7 @@
 # Spark
 
 To integrate Spark with DataHub, we provide a lightweight Java agent that listens for Spark application and job events
-and pushes metadata out to DataHub in real-time. The agent listens to events such application start/end, and
+and pushes metadata out to DataHub in real-time. The agent listens to events such as application start/end, and
 SQLExecution start/end to create pipelines (i.e. DataJob) and tasks (i.e. DataFlow) in Datahub along with lineage to
 datasets that are being read from and written to. Read on to learn how to configure this for different Spark scenarios.