VARCHAR versus TEXT when using psychopg2, sqlalchemy and redshift

I'm using SQLAlchemy backed by psychopg2 to interact with my data inside of
AWS Redshift. I'm trying to insert data and am getting a perplexing error
with respect to text vs varchar data. Here is a source snipit:

conn = get_db_connection()
keys=["a","b"]
values=["aa","bb"]

tbl_qualtrics_dim = Table('qualtrics_dim', metadata,
Column('k', String(1024), primary_key=True),
Column('v', String(1024), nullable=False)
)
metadata.create_all(conn, checkfirst=True)
ins = tbl_qualtrics_dim.insert().values(k=keys, v=values)
conn.execute(ins)

This creates the table just fine as being two columns of varchar(1024).
AWS doesn't support clob types. The last line throws an error though when
trying to insert data:

sqlalchemy.exc.ProgrammingError: (psycopg2.ProgrammingError) column "k" is
of type character varying but expression is of type text[]
HINT: You will need to rewrite or cast the expression.
[SQL: 'INSERT INTO qualtrics_dim (k, v) VALUES (%(k)s, %(v)s)']
[parameters: {'v': ['aa', 'bb'], 'k': ['a', 'b']}]

A cast as I understand it doesn't work, e.g. I change this line:

ins = tbl_qualtrics_dim.insert().values(k=cast(keys, String(1024)),
v=values)

And I get a casting error:

sqlalchemy.exc.ProgrammingError: (psycopg2.ProgrammingError) cannot cast
type text[] to character varying
[SQL: 'INSERT INTO qualtrics_dim (k, v) VALUES (CAST(%(param_1)s AS
VARCHAR(1024)), %(v)s)'] [parameters: {'v': ['aa', 'bb'], 'param_1': ['a',
'b']}]

Any hints on what might be going wrong here?

Regards,

Chris