AWS Lambda / Python Guru - Re-Architecture

Each month we receive a CSV data file that has about 5-6k records. We need that data processed and put into a MySQL data base. Here is the background and workflow: 1) We receive the raw data file as a CSV (via email) 2) We have a script that uploads that CSV to a AWS S3 bucket (called raw_data) 3) A Python Lambda is triggered that iterates over each of the records in the file.....for each record we pull a unique identifier and use that identifier to call an external api and pull in other relevant infoation 4) the results from #3 are inserted into a AWS MySQL RDS instance. 5) Move the raw data file from the raw_data bucket to a processed_data bucket So if it's working what else do we need? We'll the max time a Lambda can run is 5 mins, and the script is timing out before if finished so we need to refactor it. What we would like, is to update it to the following pattern: 1 Master lambda that reads all of the records and fans out the processing via SQS (as 5-6k messages). Then have another lambda that is triggered that will only process one message at a time. The deliverables would include: 1) All source code (the current lambda python script would need to be updated) 2) Cloud Formation Templates 3) Configured security groups such that ports, etc aren't open to the world and the only the applicable resources can talk to one another (S3, SQS, Lambda, RDS, etc) Open to fair estimates for this project