Is there a faster way to find matching features in two arrays (Python)?

I'm trying to go through each feature in one file (1 per line) and find all matching features based on one column of that line in a second file. I have this solution, which does what I want on small files, but it's very slow on big files (my files have >20,000,000 lines). Here's a sample of the two input files.

My (slow) code:

FEATUREFILE = 'S2_STARRseq_rep1_vsControl_peaks.bed'
CONSERVATIONFILEDIR = './conservation/'
with open(str(FEATUREFILE),'r') as peakFile, open('featureConservation.td',"w+") as outfile:
for line in peakFile.readlines():
    chrom = line.split('t')[0]
    startPos = int(line.split('t')[1])
    endPos = int(line.split('t')[2])
    peakName = line.split('t')[3]
    enrichVal = float(line.split('t')[4])

    #Reject negative peak starts, if they exist (sometimes this can happen w/ MACS)
    if startPos > 0:
        with open(str(CONSERVATIONFILEDIR) + str(chrom)+'.bed','r') as conservationFile:
            cumulConserv = 0.
            n = 0
            for conservLine in conservationFile.readlines():
                position = int(conservLine.split('t')[1])
                conservScore = float(conservLine.split('t')[3])
                if position >= startPos and position <= endPos:
                    cumulConserv += conservScore
                    n+=1
        featureConservation = cumulConserv/(n)
        outfile.write(str(chrom) + 't' + str(startPos) + 't' + str(endPos) + 't' + str(peakName) + 't' + str(enrichVal) + 't' + str(featureConservation) + 'n')